Project acronym 100 Archaic Genomes
Project Genome sequences from extinct hominins
Researcher (PI) Svante PaeaeBO
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Country Germany
Call Details Advanced Grant (AdG), LS2, ERC-2015-AdG
Summary Neandertals and Denisovans, an Asian group distantly related to Neandertals, are the closest evolutionary relatives of present-day humans. They are thus of direct relevance for understanding the origin of modern humans and how modern humans differ from their closest relatives. We will generate genome-wide data from a large number of Neandertal and Denisovan individuals from across their geographical and temporal range as well as from other extinct hominin groups which we may discover. This will be possible by automating highly sensitive approaches to ancient DNA extraction and DNA libraries construction that we have developed so that they can be applied to many specimens from many sites in order to identify those that contain retrievable DNA. Whenever possible we will sequence whole genomes and in other cases use DNA capture methods to generate high-quality data from representative parts of the genome. This will allow us to study the population history of Neandertals and Denisovans, elucidate how many times and where these extinct hominins contributed genes to present-day people, and the extent to which modern humans and archaic groups contributed genetically to Neandertals and Denisovans. By retrieving DNA from specimens that go back to the Middle Pleistocene we will furthermore shed light on the early history and origins of Neandertals and Denisovans.
Summary
Neandertals and Denisovans, an Asian group distantly related to Neandertals, are the closest evolutionary relatives of present-day humans. They are thus of direct relevance for understanding the origin of modern humans and how modern humans differ from their closest relatives. We will generate genome-wide data from a large number of Neandertal and Denisovan individuals from across their geographical and temporal range as well as from other extinct hominin groups which we may discover. This will be possible by automating highly sensitive approaches to ancient DNA extraction and DNA libraries construction that we have developed so that they can be applied to many specimens from many sites in order to identify those that contain retrievable DNA. Whenever possible we will sequence whole genomes and in other cases use DNA capture methods to generate high-quality data from representative parts of the genome. This will allow us to study the population history of Neandertals and Denisovans, elucidate how many times and where these extinct hominins contributed genes to present-day people, and the extent to which modern humans and archaic groups contributed genetically to Neandertals and Denisovans. By retrieving DNA from specimens that go back to the Middle Pleistocene we will furthermore shed light on the early history and origins of Neandertals and Denisovans.
Max ERC Funding
2 350 000 €
Duration
Start date: 2016-11-01, End date: 2021-10-31
Project acronym 1stProposal
Project An alternative development of analytic number theory and applications
Researcher (PI) ANDREW Granville
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Country United Kingdom
Call Details Advanced Grant (AdG), PE1, ERC-2014-ADG
Summary The traditional (Riemann) approach to analytic number theory uses the zeros of zeta functions. This requires the associated multiplicative function, say f(n), to have special enough properties that the associated Dirichlet series may be analytically continued. In this proposal we continue to develop an approach which requires less of the multiplicative function, linking the original question with the mean value of f. Such techniques have been around for a long time but have generally been regarded as “ad hoc”. In this project we aim to show that one can develop a coherent approach to the whole subject, not only reproving all of the old results, but also many new ones that appear inaccessible to traditional methods.
Our first goal is to complete a monograph yielding a reworking of all the classical theory using these new methods and then to push forward in new directions. The most important is to extend these techniques to GL(n) L-functions, which we hope will now be feasible having found the correct framework in which to proceed. Since we rarely know how to analytically continue such L-functions this could be of great benefit to the subject.
We are developing the large sieve so that it can be used for individual moduli, and will determine a strong form of that. Also a new method to give asymptotics for mean values, when they are not too small.
We wish to incorporate techniques of analytic number theory into our theory, for example recent advances on mean values of Dirichlet polynomials. Also the recent breakthroughs on the sieve suggest strong links that need further exploration.
Additive combinatorics yields important results in many areas. There are strong analogies between its results, and those for multiplicative functions, especially in large value spectrum theory, and its applications. We hope to develop these further.
Much of this is joint work with K Soundararajan of Stanford University.
Summary
The traditional (Riemann) approach to analytic number theory uses the zeros of zeta functions. This requires the associated multiplicative function, say f(n), to have special enough properties that the associated Dirichlet series may be analytically continued. In this proposal we continue to develop an approach which requires less of the multiplicative function, linking the original question with the mean value of f. Such techniques have been around for a long time but have generally been regarded as “ad hoc”. In this project we aim to show that one can develop a coherent approach to the whole subject, not only reproving all of the old results, but also many new ones that appear inaccessible to traditional methods.
Our first goal is to complete a monograph yielding a reworking of all the classical theory using these new methods and then to push forward in new directions. The most important is to extend these techniques to GL(n) L-functions, which we hope will now be feasible having found the correct framework in which to proceed. Since we rarely know how to analytically continue such L-functions this could be of great benefit to the subject.
We are developing the large sieve so that it can be used for individual moduli, and will determine a strong form of that. Also a new method to give asymptotics for mean values, when they are not too small.
We wish to incorporate techniques of analytic number theory into our theory, for example recent advances on mean values of Dirichlet polynomials. Also the recent breakthroughs on the sieve suggest strong links that need further exploration.
Additive combinatorics yields important results in many areas. There are strong analogies between its results, and those for multiplicative functions, especially in large value spectrum theory, and its applications. We hope to develop these further.
Much of this is joint work with K Soundararajan of Stanford University.
Max ERC Funding
2 011 742 €
Duration
Start date: 2015-08-01, End date: 2020-07-31
Project acronym 3DEpi
Project Transgenerational epigenetic inheritance of chromatin states : the role of Polycomb and 3D chromosome architecture
Researcher (PI) Giacomo CAVALLI
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Advanced Grant (AdG), LS2, ERC-2017-ADG
Summary Epigenetic inheritance entails transmission of phenotypic traits not encoded in the DNA sequence and, in the most extreme case, Transgenerational Epigenetic Inheritance (TEI) involves transmission of memory through multiple generations. Very little is known on the mechanisms governing TEI and this is the subject of the present proposal. By transiently enhancing long-range chromatin interactions, we recently established isogenic Drosophila epilines that carry stable alternative epialleles, defined by differential levels of the Polycomb-dependent H3K27me3 mark. Furthermore, we extended our paradigm to natural phenotypes. These are ideal systems to study the role of Polycomb group (PcG) proteins and other components in regulating nuclear organization and epigenetic inheritance of chromatin states. The present project conjugates genetics, epigenomics, imaging and molecular biology to reach three critical aims.
Aim 1: Analysis of the molecular mechanisms regulating Polycomb-mediated TEI. We will identify the DNA, protein and RNA components that trigger and maintain transgenerational chromatin inheritance as well as their mechanisms of action.
Aim 2: Role of 3D genome organization in the regulation of TEI. We will analyze the developmental dynamics of TEI-inducing long-range chromatin interactions, identify chromatin components mediating 3D chromatin contacts and characterize their function in the TEI process.
Aim 3: Identification of a broader role of TEI during development. TEI might reflect a normal role of PcG components in the transmission of parental chromatin onto the next embryonic generation. We will explore this possibility by establishing other TEI paradigms and by relating TEI to the normal PcG function in these systems and in normal development.
This research program will unravel the biological significance and the molecular underpinnings of TEI and lead the way towards establishing this area of research into a consolidated scientific discipline.
Summary
Epigenetic inheritance entails transmission of phenotypic traits not encoded in the DNA sequence and, in the most extreme case, Transgenerational Epigenetic Inheritance (TEI) involves transmission of memory through multiple generations. Very little is known on the mechanisms governing TEI and this is the subject of the present proposal. By transiently enhancing long-range chromatin interactions, we recently established isogenic Drosophila epilines that carry stable alternative epialleles, defined by differential levels of the Polycomb-dependent H3K27me3 mark. Furthermore, we extended our paradigm to natural phenotypes. These are ideal systems to study the role of Polycomb group (PcG) proteins and other components in regulating nuclear organization and epigenetic inheritance of chromatin states. The present project conjugates genetics, epigenomics, imaging and molecular biology to reach three critical aims.
Aim 1: Analysis of the molecular mechanisms regulating Polycomb-mediated TEI. We will identify the DNA, protein and RNA components that trigger and maintain transgenerational chromatin inheritance as well as their mechanisms of action.
Aim 2: Role of 3D genome organization in the regulation of TEI. We will analyze the developmental dynamics of TEI-inducing long-range chromatin interactions, identify chromatin components mediating 3D chromatin contacts and characterize their function in the TEI process.
Aim 3: Identification of a broader role of TEI during development. TEI might reflect a normal role of PcG components in the transmission of parental chromatin onto the next embryonic generation. We will explore this possibility by establishing other TEI paradigms and by relating TEI to the normal PcG function in these systems and in normal development.
This research program will unravel the biological significance and the molecular underpinnings of TEI and lead the way towards establishing this area of research into a consolidated scientific discipline.
Max ERC Funding
2 500 000 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym 4D-EEG
Project 4D-EEG: A new tool to investigate the spatial and temporal activity patterns in the brain
Researcher (PI) Franciscus C.T. Van Der Helm
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Country Netherlands
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Our first goal is to develop a new tool to determine brain activity with a high temporal (< 1 msec) and spatial (about 2 mm) resolution with the focus on motor control. High density EEG (up to 256 electrodes) will be used for EEG source localization. Advanced force-controlled robot manipulators will be used to impose continuous force perturbations to the joints. Advanced closed-loop system identification algorithms will identify the dynamic EEG response of multiple brain areas to the perturbation, leading to a functional interpretation of EEG. The propagation of the signal in time and 3D space through the cortex can be monitored: 4D-EEG. Preliminary experiments with EEG localization have shown that the continuous force perturbations resulted in a better signal-to-noise ratio and coherence than the current method using transient perturbations..
4D-EEG will be a direct measure of the neural activity in the brain with an excellent temporal response and easy to use in combination with motor control tasks. The new 4D-EEG method is expected to provide a breakthrough in comparison to functional MRI (fMRI) when elucidating the meaning of cortical map plasticity in motor learning.
Our second goal is to generate and validate new hypotheses about the longitudinal relationship between motor learning and cortical map plasticity by clinically using 4D-EEG in an intensive, repeated measurement design in patients suffering from a stroke. The application of 4D-EEG combined with haptic robots will allow us to discover how dynamics in cortical map plasticity are related with upper limb recovery after stroke in terms of neural repair and using behavioral compensation strategies while performing a meaningful motor tasks.. The non-invasive 4D-EEG technique combined with haptic robots will open the window about what and how patients (re)learn when showing motor recovery after stroke in order to allow us to develop more effective patient-tailored therapies in neuro-rehabilitation.
Summary
Our first goal is to develop a new tool to determine brain activity with a high temporal (< 1 msec) and spatial (about 2 mm) resolution with the focus on motor control. High density EEG (up to 256 electrodes) will be used for EEG source localization. Advanced force-controlled robot manipulators will be used to impose continuous force perturbations to the joints. Advanced closed-loop system identification algorithms will identify the dynamic EEG response of multiple brain areas to the perturbation, leading to a functional interpretation of EEG. The propagation of the signal in time and 3D space through the cortex can be monitored: 4D-EEG. Preliminary experiments with EEG localization have shown that the continuous force perturbations resulted in a better signal-to-noise ratio and coherence than the current method using transient perturbations..
4D-EEG will be a direct measure of the neural activity in the brain with an excellent temporal response and easy to use in combination with motor control tasks. The new 4D-EEG method is expected to provide a breakthrough in comparison to functional MRI (fMRI) when elucidating the meaning of cortical map plasticity in motor learning.
Our second goal is to generate and validate new hypotheses about the longitudinal relationship between motor learning and cortical map plasticity by clinically using 4D-EEG in an intensive, repeated measurement design in patients suffering from a stroke. The application of 4D-EEG combined with haptic robots will allow us to discover how dynamics in cortical map plasticity are related with upper limb recovery after stroke in terms of neural repair and using behavioral compensation strategies while performing a meaningful motor tasks.. The non-invasive 4D-EEG technique combined with haptic robots will open the window about what and how patients (re)learn when showing motor recovery after stroke in order to allow us to develop more effective patient-tailored therapies in neuro-rehabilitation.
Max ERC Funding
3 477 202 €
Duration
Start date: 2012-06-01, End date: 2017-05-31
Project acronym AAMOT
Project Arithmetic of automorphic motives
Researcher (PI) Michael Harris
Host Institution (HI) INSTITUT DES HAUTES ETUDES SCIENTIFIQUES
Country France
Call Details Advanced Grant (AdG), PE1, ERC-2011-ADG_20110209
Summary The primary purpose of this project is to build on recent spectacular progress in the Langlands program to study the arithmetic properties of automorphic motives constructed in the cohomology of Shimura varieties. Because automorphic methods are available to study the L-functions of these motives, which include elliptic curves and certain families of Calabi-Yau varieties over totally real fields (possibly after base change), they represent the most accessible class of varieties for which one can hope to verify fundamental conjectures on special values of L-functions, including Deligne's conjecture and the Main Conjecture of Iwasawa theory. Immediate goals include the proof of irreducibility of automorphic Galois representations; the establishment of period relations for automorphic and potentially automorphic realizations of motives in the cohomology of distinct Shimura varieties; the construction of p-adic L-functions for these and related motives, notably adjoint and tensor product L-functions in p-adic families; and the geometrization of the p-adic and mod p Langlands program. All four goals, as well as the others mentioned in the body of the proposal, are interconnected; the final goal provides a bridge to related work in geometric representation theory, algebraic geometry, and mathematical physics.
Summary
The primary purpose of this project is to build on recent spectacular progress in the Langlands program to study the arithmetic properties of automorphic motives constructed in the cohomology of Shimura varieties. Because automorphic methods are available to study the L-functions of these motives, which include elliptic curves and certain families of Calabi-Yau varieties over totally real fields (possibly after base change), they represent the most accessible class of varieties for which one can hope to verify fundamental conjectures on special values of L-functions, including Deligne's conjecture and the Main Conjecture of Iwasawa theory. Immediate goals include the proof of irreducibility of automorphic Galois representations; the establishment of period relations for automorphic and potentially automorphic realizations of motives in the cohomology of distinct Shimura varieties; the construction of p-adic L-functions for these and related motives, notably adjoint and tensor product L-functions in p-adic families; and the geometrization of the p-adic and mod p Langlands program. All four goals, as well as the others mentioned in the body of the proposal, are interconnected; the final goal provides a bridge to related work in geometric representation theory, algebraic geometry, and mathematical physics.
Max ERC Funding
1 491 348 €
Duration
Start date: 2012-06-01, End date: 2018-05-31
Project acronym ABEP
Project Asset Bubbles and Economic Policy
Researcher (PI) Jaume Ventura Fontanet
Host Institution (HI) Centre de Recerca en Economia Internacional (CREI)
Country Spain
Call Details Advanced Grant (AdG), SH1, ERC-2009-AdG
Summary Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.
Summary
Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.
Max ERC Funding
1 000 000 €
Duration
Start date: 2010-04-01, End date: 2015-03-31
Project acronym ACCOMPLI
Project Assembly and maintenance of a co-regulated chromosomal compartment
Researcher (PI) Peter Burkhard Becker
Host Institution (HI) LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Country Germany
Call Details Advanced Grant (AdG), LS2, ERC-2011-ADG_20110310
Summary "Eukaryotic nuclei are organised into functional compartments, – local microenvironments that are enriched in certain molecules or biochemical activities and therefore specify localised functional outputs. Our study seeks to unveil fundamental principles of co-regulation of genes in a chromo¬somal compartment and the preconditions for homeostasis of such a compartment in the dynamic nuclear environment.
The dosage-compensated X chromosome of male Drosophila flies satisfies the criteria for a functional com¬partment. It is rendered structurally distinct from all other chromosomes by association of a regulatory ribonucleoprotein ‘Dosage Compensation Complex’ (DCC), enrichment of histone modifications and global decondensation. As a result, most genes on the X chromosome are co-ordinately activated. Autosomal genes inserted into the X acquire X-chromosomal features and are subject to the X-specific regulation.
We seek to uncover the molecular principles that initiate, establish and maintain the dosage-compensated chromosome. We will follow the kinetics of DCC assembly and the timing of association with different types of chromosomal targets in nuclei with high spatial resolution afforded by sub-wavelength microscopy and deep sequencing of DNA binding sites. We will characterise DCC sub-complexes with respect to their roles as kinetic assembly intermediates or as representations of local, functional heterogeneity. We will evaluate the roles of a DCC- novel ubiquitin ligase activity for homeostasis.
Crucial to the recruitment of the DCC and its distribution to target genes are non-coding roX RNAs that are transcribed from the X. We will determine the secondary structure ‘signatures’ of roX RNAs in vitro and determine the binding sites of the protein subunits in vivo. By biochemical and cellular reconstitution will test the hypothesis that roX-encoded RNA aptamers orchestrate the assembly of the DCC and contribute to the exquisite targeting of the complex."
Summary
"Eukaryotic nuclei are organised into functional compartments, – local microenvironments that are enriched in certain molecules or biochemical activities and therefore specify localised functional outputs. Our study seeks to unveil fundamental principles of co-regulation of genes in a chromo¬somal compartment and the preconditions for homeostasis of such a compartment in the dynamic nuclear environment.
The dosage-compensated X chromosome of male Drosophila flies satisfies the criteria for a functional com¬partment. It is rendered structurally distinct from all other chromosomes by association of a regulatory ribonucleoprotein ‘Dosage Compensation Complex’ (DCC), enrichment of histone modifications and global decondensation. As a result, most genes on the X chromosome are co-ordinately activated. Autosomal genes inserted into the X acquire X-chromosomal features and are subject to the X-specific regulation.
We seek to uncover the molecular principles that initiate, establish and maintain the dosage-compensated chromosome. We will follow the kinetics of DCC assembly and the timing of association with different types of chromosomal targets in nuclei with high spatial resolution afforded by sub-wavelength microscopy and deep sequencing of DNA binding sites. We will characterise DCC sub-complexes with respect to their roles as kinetic assembly intermediates or as representations of local, functional heterogeneity. We will evaluate the roles of a DCC- novel ubiquitin ligase activity for homeostasis.
Crucial to the recruitment of the DCC and its distribution to target genes are non-coding roX RNAs that are transcribed from the X. We will determine the secondary structure ‘signatures’ of roX RNAs in vitro and determine the binding sites of the protein subunits in vivo. By biochemical and cellular reconstitution will test the hypothesis that roX-encoded RNA aptamers orchestrate the assembly of the DCC and contribute to the exquisite targeting of the complex."
Max ERC Funding
2 482 770 €
Duration
Start date: 2012-02-01, End date: 2017-01-31
Project acronym ACROSS
Project 3D Reconstruction and Modeling across Different Levels of Abstraction
Researcher (PI) Leif Kobbelt
Host Institution (HI) RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN
Country Germany
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Summary
"Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Max ERC Funding
2 482 000 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym Actanthrope
Project Computational Foundations of Anthropomorphic Action
Researcher (PI) Jean Paul Laumond
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Advanced Grant (AdG), PE7, ERC-2013-ADG
Summary Actanthrope intends to promote a neuro-robotics perspective to explore original models of anthropomorphic action. The project targets contributions to humanoid robot autonomy (for rescue and service robotics), to advanced human body simulation (for applications in ergonomics), and to a new theory of embodied intelligence (by promoting a motion-based semiotics of the human action).
Actions take place in the physical space while they originate in the –robot or human– sensory-motor space. Geometry is the core abstraction that makes the link between these spaces. Considering that the structure of actions inherits from that of the body, the underlying intuition is that actions can be segmented within discrete sub-spaces lying in the entire continuous posture space. Such sub-spaces are viewed as symbols bridging deliberative reasoning and reactive control. Actanthrope argues that geometric approaches to motion segmentation and generation as promising and innovative routes to explore embodied intelligence:
- Motion segmentation: what are the sub-manifolds that define the structure of a given action?
- Motion generation: among all the solution paths within a given sub-manifold, what is the underlying law that makes the selection?
In Robotics these questions are related to the competition between abstract symbol manipulation and physical signal processing. In Computational Neuroscience the questions refer to the quest of motion invariants. The ambition of the project is to promote a dual perspective: exploring the computational foundations of human action to make better robots, while simultaneously doing better robotics to better understand human action.
A unique “Anthropomorphic Action Factory” supports the methodology. It aims at attracting to a single lab, researchers with complementary know-how and solid mathematical background. All of them will benefit from unique equipments, while being stimulated by four challenges dealing with locomotion and manipulation actions.
Summary
Actanthrope intends to promote a neuro-robotics perspective to explore original models of anthropomorphic action. The project targets contributions to humanoid robot autonomy (for rescue and service robotics), to advanced human body simulation (for applications in ergonomics), and to a new theory of embodied intelligence (by promoting a motion-based semiotics of the human action).
Actions take place in the physical space while they originate in the –robot or human– sensory-motor space. Geometry is the core abstraction that makes the link between these spaces. Considering that the structure of actions inherits from that of the body, the underlying intuition is that actions can be segmented within discrete sub-spaces lying in the entire continuous posture space. Such sub-spaces are viewed as symbols bridging deliberative reasoning and reactive control. Actanthrope argues that geometric approaches to motion segmentation and generation as promising and innovative routes to explore embodied intelligence:
- Motion segmentation: what are the sub-manifolds that define the structure of a given action?
- Motion generation: among all the solution paths within a given sub-manifold, what is the underlying law that makes the selection?
In Robotics these questions are related to the competition between abstract symbol manipulation and physical signal processing. In Computational Neuroscience the questions refer to the quest of motion invariants. The ambition of the project is to promote a dual perspective: exploring the computational foundations of human action to make better robots, while simultaneously doing better robotics to better understand human action.
A unique “Anthropomorphic Action Factory” supports the methodology. It aims at attracting to a single lab, researchers with complementary know-how and solid mathematical background. All of them will benefit from unique equipments, while being stimulated by four challenges dealing with locomotion and manipulation actions.
Max ERC Funding
2 500 000 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym ADDECCO
Project Adaptive Schemes for Deterministic and Stochastic Flow Problems
Researcher (PI) Remi Abgrall
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Country France
Call Details Advanced Grant (AdG), PE1, ERC-2008-AdG
Summary The numerical simulation of complex compressible flow problem is still a challenge nowaday even for simple models. In our opinion, the most important hard points that need currently to be tackled and solved is how to obtain stable, scalable, very accurate, easy to code and to maintain schemes on complex geometries. The method should easily handle mesh refinement, even near the boundary where the most interesting engineering quantities have to be evaluated. Unsteady uncertainties in the model, for example in the geometry or the boundary conditions should represented efficiently.This proposal goal is to design, develop and evaluate solutions to each of the above problems. Our work program will lead to significant breakthroughs for flow simulations. More specifically, we propose to work on 3 connected problems: 1-A class of very high order numerical schemes able to easily deal with the geometry of boundaries and still can solve steep problems. The geometry is generally defined by CAD tools. The output is used to generate a mesh which is then used by the scheme. Hence, any mesh refinement process is disconnected from the CAD, a situation that prevents the spread of mesh adaptation techniques in industry! 2-A class of very high order numerical schemes which can utilize possibly solution dependant basis functions in order to lower the number of degrees of freedom, for example to compute accurately boundary layers with low resolutions. 3-A general non intrusive technique for handling uncertainties in order to deal with irregular probability density functions (pdf) and also to handle pdf that may evolve in time, for example thanks to an optimisation loop. The curse of dimensionality will be dealt thanks Harten's multiresolution method combined with sparse grid methods. Currently, and up to our knowledge, no scheme has each of these properties. This research program will have an impact on numerical schemes and industrial applications.
Summary
The numerical simulation of complex compressible flow problem is still a challenge nowaday even for simple models. In our opinion, the most important hard points that need currently to be tackled and solved is how to obtain stable, scalable, very accurate, easy to code and to maintain schemes on complex geometries. The method should easily handle mesh refinement, even near the boundary where the most interesting engineering quantities have to be evaluated. Unsteady uncertainties in the model, for example in the geometry or the boundary conditions should represented efficiently.This proposal goal is to design, develop and evaluate solutions to each of the above problems. Our work program will lead to significant breakthroughs for flow simulations. More specifically, we propose to work on 3 connected problems: 1-A class of very high order numerical schemes able to easily deal with the geometry of boundaries and still can solve steep problems. The geometry is generally defined by CAD tools. The output is used to generate a mesh which is then used by the scheme. Hence, any mesh refinement process is disconnected from the CAD, a situation that prevents the spread of mesh adaptation techniques in industry! 2-A class of very high order numerical schemes which can utilize possibly solution dependant basis functions in order to lower the number of degrees of freedom, for example to compute accurately boundary layers with low resolutions. 3-A general non intrusive technique for handling uncertainties in order to deal with irregular probability density functions (pdf) and also to handle pdf that may evolve in time, for example thanks to an optimisation loop. The curse of dimensionality will be dealt thanks Harten's multiresolution method combined with sparse grid methods. Currently, and up to our knowledge, no scheme has each of these properties. This research program will have an impact on numerical schemes and industrial applications.
Max ERC Funding
1 432 769 €
Duration
Start date: 2008-12-01, End date: 2013-11-30
Project acronym AdOMiS
Project Adaptive Optical Microscopy Systems: Unifying theory, practice and applications
Researcher (PI) Martin BOOTH
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Country United Kingdom
Call Details Advanced Grant (AdG), PE7, ERC-2015-AdG
Summary Recent technological advances in optical microscopy have vastly broadened the possibilities for applications in the biomedical sciences. Fluorescence microscopy is the central tool for investigation of molecular structures and dynamics that take place in the cellular and tissue environment. Coupled with progress in labeling methods, these microscopes permit observation of biological structures and processes with unprecedented sensitivity and resolution. This work has been enabled by the engineering development of diverse optical systems that provide different capabilities for the imaging toolkit. All such methods rely upon high fidelity optics to provide optimal resolution and efficiency, but they all suffer from aberrations caused by refractive index variations within the specimen. It is widely accepted that in many applications this fundamental problem prevents optimum operation and limits capability. Adaptive optics (AO) has been introduced to overcome these limitations by correcting aberrations and a range of demonstrations has shown clearly its potential. Indeed, it shows great promise to improve virtually all types of research or commercial microscopes, but significant challenges must still be met before AO can be widely implemented in routine imaging. Current advances are being made through development of bespoke AO solutions to individual imaging tasks. However, the diversity of microscopy methods means that individual solutions are often not translatable to other systems. This proposal is directed towards the creation of theoretical and practical frameworks that tie together AO concepts and provide a suite of scientific tools with broad application. This will be achieved through a systems approach that encompasses theoretical modelling, optical engineering and the requirements of biological applications. Additional outputs will include practical designs, operating protocols and software algorithms that will support next generation AO microscope systems.
Summary
Recent technological advances in optical microscopy have vastly broadened the possibilities for applications in the biomedical sciences. Fluorescence microscopy is the central tool for investigation of molecular structures and dynamics that take place in the cellular and tissue environment. Coupled with progress in labeling methods, these microscopes permit observation of biological structures and processes with unprecedented sensitivity and resolution. This work has been enabled by the engineering development of diverse optical systems that provide different capabilities for the imaging toolkit. All such methods rely upon high fidelity optics to provide optimal resolution and efficiency, but they all suffer from aberrations caused by refractive index variations within the specimen. It is widely accepted that in many applications this fundamental problem prevents optimum operation and limits capability. Adaptive optics (AO) has been introduced to overcome these limitations by correcting aberrations and a range of demonstrations has shown clearly its potential. Indeed, it shows great promise to improve virtually all types of research or commercial microscopes, but significant challenges must still be met before AO can be widely implemented in routine imaging. Current advances are being made through development of bespoke AO solutions to individual imaging tasks. However, the diversity of microscopy methods means that individual solutions are often not translatable to other systems. This proposal is directed towards the creation of theoretical and practical frameworks that tie together AO concepts and provide a suite of scientific tools with broad application. This will be achieved through a systems approach that encompasses theoretical modelling, optical engineering and the requirements of biological applications. Additional outputs will include practical designs, operating protocols and software algorithms that will support next generation AO microscope systems.
Max ERC Funding
3 234 789 €
Duration
Start date: 2016-09-01, End date: 2022-02-28
Project acronym ADORA
Project Asymptotic approach to spatial and dynamical organizations
Researcher (PI) Benoit PERTHAME
Host Institution (HI) SORBONNE UNIVERSITE
Country France
Call Details Advanced Grant (AdG), PE1, ERC-2016-ADG
Summary The understanding of spatial, social and dynamical organization of large numbers of agents is presently a fundamental issue in modern science. ADORA focuses on problems motivated by biology because, more than anywhere else, access to precise and many data has opened the route to novel and complex biomathematical models. The problems we address are written in terms of nonlinear partial differential equations. The flux-limited Keller-Segel system, the integrate-and-fire Fokker-Planck equation, kinetic equations with internal state, nonlocal parabolic equations and constrained Hamilton-Jacobi equations are among examples of the equations under investigation.
The role of mathematics is not only to understand the analytical structure of these new problems, but it is also to explain the qualitative behavior of solutions and to quantify their properties. The challenge arises here because these goals should be achieved through a hierarchy of scales. Indeed, the problems under consideration share the common feature that the large scale behavior cannot be understood precisely without access to a hierarchy of finer scales, down to the individual behavior and sometimes its molecular determinants.
Major difficulties arise because the numerous scales present in these equations have to be discovered and singularities appear in the asymptotic process which yields deep compactness obstructions. Our vision is that the complexity inherent to models of biology can be enlightened by mathematical analysis and a classification of the possible asymptotic regimes.
However an enormous effort is needed to uncover the equations intimate mathematical structures, and bring them at the level of conceptual understanding they deserve being given the applications motivating these questions which range from medical science or neuroscience to cell biology.
Summary
The understanding of spatial, social and dynamical organization of large numbers of agents is presently a fundamental issue in modern science. ADORA focuses on problems motivated by biology because, more than anywhere else, access to precise and many data has opened the route to novel and complex biomathematical models. The problems we address are written in terms of nonlinear partial differential equations. The flux-limited Keller-Segel system, the integrate-and-fire Fokker-Planck equation, kinetic equations with internal state, nonlocal parabolic equations and constrained Hamilton-Jacobi equations are among examples of the equations under investigation.
The role of mathematics is not only to understand the analytical structure of these new problems, but it is also to explain the qualitative behavior of solutions and to quantify their properties. The challenge arises here because these goals should be achieved through a hierarchy of scales. Indeed, the problems under consideration share the common feature that the large scale behavior cannot be understood precisely without access to a hierarchy of finer scales, down to the individual behavior and sometimes its molecular determinants.
Major difficulties arise because the numerous scales present in these equations have to be discovered and singularities appear in the asymptotic process which yields deep compactness obstructions. Our vision is that the complexity inherent to models of biology can be enlightened by mathematical analysis and a classification of the possible asymptotic regimes.
However an enormous effort is needed to uncover the equations intimate mathematical structures, and bring them at the level of conceptual understanding they deserve being given the applications motivating these questions which range from medical science or neuroscience to cell biology.
Max ERC Funding
2 192 500 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
Project acronym AFMIDMOA
Project "Applying Fundamental Mathematics in Discrete Mathematics, Optimization, and Algorithmics"
Researcher (PI) Alexander Schrijver
Host Institution (HI) UNIVERSITEIT VAN AMSTERDAM
Country Netherlands
Call Details Advanced Grant (AdG), PE1, ERC-2013-ADG
Summary "This proposal aims at strengthening the connections between more fundamentally oriented areas of mathematics like algebra, geometry, analysis, and topology, and the more applied oriented and more recently emerging disciplines of discrete mathematics, optimization, and algorithmics.
The overall goal of the project is to obtain, with methods from fundamental mathematics, new effective tools to unravel the complexity of structures like graphs, networks, codes, knots, polynomials, and tensors, and to get a grip on such complex structures by new efficient characterizations, sharper bounds, and faster algorithms.
In the last few years, there have been several new developments where methods from representation theory, invariant theory, algebraic geometry, measure theory, functional analysis, and topology found new applications in discrete mathematics and optimization, both theoretically and algorithmically. Among the typical application areas are networks, coding, routing, timetabling, statistical and quantum physics, and computer science.
The project focuses in particular on:
A. Understanding partition functions with invariant theory and algebraic geometry
B. Graph limits, regularity, Hilbert spaces, and low rank approximation of polynomials
C. Reducing complexity in optimization by exploiting symmetry with representation theory
D. Reducing complexity in discrete optimization by homotopy and cohomology
These research modules are interconnected by themes like symmetry, regularity, and complexity, and by common methods from algebra, analysis, geometry, and topology."
Summary
"This proposal aims at strengthening the connections between more fundamentally oriented areas of mathematics like algebra, geometry, analysis, and topology, and the more applied oriented and more recently emerging disciplines of discrete mathematics, optimization, and algorithmics.
The overall goal of the project is to obtain, with methods from fundamental mathematics, new effective tools to unravel the complexity of structures like graphs, networks, codes, knots, polynomials, and tensors, and to get a grip on such complex structures by new efficient characterizations, sharper bounds, and faster algorithms.
In the last few years, there have been several new developments where methods from representation theory, invariant theory, algebraic geometry, measure theory, functional analysis, and topology found new applications in discrete mathematics and optimization, both theoretically and algorithmically. Among the typical application areas are networks, coding, routing, timetabling, statistical and quantum physics, and computer science.
The project focuses in particular on:
A. Understanding partition functions with invariant theory and algebraic geometry
B. Graph limits, regularity, Hilbert spaces, and low rank approximation of polynomials
C. Reducing complexity in optimization by exploiting symmetry with representation theory
D. Reducing complexity in discrete optimization by homotopy and cohomology
These research modules are interconnected by themes like symmetry, regularity, and complexity, and by common methods from algebra, analysis, geometry, and topology."
Max ERC Funding
2 001 598 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym ALEXANDRIA
Project "Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives"
Researcher (PI) Wolfgang Nejdl
Host Institution (HI) GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER
Country Germany
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Significant parts of our cultural heritage are produced on the Web, yet only insufficient opportunities exist for accessing and exploring the past of the Web. The ALEXANDRIA project aims to develop models, tools and techniques necessary to archive and index relevant parts of the Web, and to retrieve and explore this information in a meaningful way. While the easy accessibility to the current Web is a good baseline, optimal access to Web archives requires new models and algorithms for retrieval, exploration, and analytics which go far beyond what is needed to access the current state of the Web. This includes taking into account the unique temporal dimension of Web archives, structured semantic information already available on the Web, as well as social media and network information.
Within ALEXANDRIA, we will significantly advance semantic and time-based indexing for Web archives using human-compiled knowledge available on the Web, to efficiently index, retrieve and explore information about entities and events from the past. In doing so, we will focus on the concurrent evolution of this knowledge and the Web content to be indexed, and take into account diversity and incompleteness of this knowledge. We will further investigate mixed crowd- and machine-based Web analytics to support long- running and collaborative retrieval and analysis processes on Web archives. Usage of implicit human feedback will be essential to provide better indexing through insights during the analysis process and to better focus harvesting of content.
The ALEXANDRIA Testbed will provide an important context for research, exploration and evaluation of the concepts, methods and algorithms developed in this project, and will provide both relevant collections and algorithms that enable further research on and practical application of our research results to existing archives like the Internet Archive, the Internet Memory Foundation and Web archives maintained by European national libraries."
Summary
"Significant parts of our cultural heritage are produced on the Web, yet only insufficient opportunities exist for accessing and exploring the past of the Web. The ALEXANDRIA project aims to develop models, tools and techniques necessary to archive and index relevant parts of the Web, and to retrieve and explore this information in a meaningful way. While the easy accessibility to the current Web is a good baseline, optimal access to Web archives requires new models and algorithms for retrieval, exploration, and analytics which go far beyond what is needed to access the current state of the Web. This includes taking into account the unique temporal dimension of Web archives, structured semantic information already available on the Web, as well as social media and network information.
Within ALEXANDRIA, we will significantly advance semantic and time-based indexing for Web archives using human-compiled knowledge available on the Web, to efficiently index, retrieve and explore information about entities and events from the past. In doing so, we will focus on the concurrent evolution of this knowledge and the Web content to be indexed, and take into account diversity and incompleteness of this knowledge. We will further investigate mixed crowd- and machine-based Web analytics to support long- running and collaborative retrieval and analysis processes on Web archives. Usage of implicit human feedback will be essential to provide better indexing through insights during the analysis process and to better focus harvesting of content.
The ALEXANDRIA Testbed will provide an important context for research, exploration and evaluation of the concepts, methods and algorithms developed in this project, and will provide both relevant collections and algorithms that enable further research on and practical application of our research results to existing archives like the Internet Archive, the Internet Memory Foundation and Web archives maintained by European national libraries."
Max ERC Funding
2 493 600 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym ALEXANDRIA
Project Large-Scale Formal Proof for the Working Mathematician
Researcher (PI) Lawrence PAULSON
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), PE6, ERC-2016-ADG
Summary Mathematical proofs have always been prone to error. Today, proofs can be hundreds of pages long and combine results from many specialisms, making them almost impossible to check. One solution is to deploy modern verification technology. Interactive theorem provers have demonstrated their potential as vehicles for formalising mathematics through achievements such as the verification of the Kepler Conjecture. Proofs done using such tools reach a high standard of correctness.
However, existing theorem provers are unsuitable for mathematics. Their formal proofs are unreadable. They struggle to do simple tasks, such as evaluating limits. They lack much basic mathematics, and the material they do have is difficult to locate and apply.
ALEXANDRIA will create a proof development environment attractive to working mathematicians, utilising the best technology available across computer science. Its focus will be the management and use of large-scale mathematical knowledge, both theorems and algorithms. The project will employ mathematicians to investigate the formalisation of mathematics in practice. Our already substantial formalised libraries will serve as the starting point. They will be extended and annotated to support sophisticated searches. Techniques will be borrowed from machine learning, information retrieval and natural language processing. Algorithms will be treated similarly: ALEXANDRIA will help users find and invoke the proof methods and algorithms appropriate for the task.
ALEXANDRIA will provide (1) comprehensive formal mathematical libraries; (2) search within libraries, and the mining of libraries for proof patterns; (3) automated support for the construction of large formal proofs; (4) sound and practical computer algebra tools.
ALEXANDRIA will be based on legible structured proofs. Formal proofs should be not mere code, but a machine-checkable form of communication between mathematicians.
Summary
Mathematical proofs have always been prone to error. Today, proofs can be hundreds of pages long and combine results from many specialisms, making them almost impossible to check. One solution is to deploy modern verification technology. Interactive theorem provers have demonstrated their potential as vehicles for formalising mathematics through achievements such as the verification of the Kepler Conjecture. Proofs done using such tools reach a high standard of correctness.
However, existing theorem provers are unsuitable for mathematics. Their formal proofs are unreadable. They struggle to do simple tasks, such as evaluating limits. They lack much basic mathematics, and the material they do have is difficult to locate and apply.
ALEXANDRIA will create a proof development environment attractive to working mathematicians, utilising the best technology available across computer science. Its focus will be the management and use of large-scale mathematical knowledge, both theorems and algorithms. The project will employ mathematicians to investigate the formalisation of mathematics in practice. Our already substantial formalised libraries will serve as the starting point. They will be extended and annotated to support sophisticated searches. Techniques will be borrowed from machine learning, information retrieval and natural language processing. Algorithms will be treated similarly: ALEXANDRIA will help users find and invoke the proof methods and algorithms appropriate for the task.
ALEXANDRIA will provide (1) comprehensive formal mathematical libraries; (2) search within libraries, and the mining of libraries for proof patterns; (3) automated support for the construction of large formal proofs; (4) sound and practical computer algebra tools.
ALEXANDRIA will be based on legible structured proofs. Formal proofs should be not mere code, but a machine-checkable form of communication between mathematicians.
Max ERC Funding
2 430 140 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
Project acronym ALGAME
Project Algorithms, Games, Mechanisms, and the Price of Anarchy
Researcher (PI) Elias Koutsoupias
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Country United Kingdom
Call Details Advanced Grant (AdG), PE6, ERC-2012-ADG_20120216
Summary The objective of this proposal is to bring together a local team of young researchers who will work closely with international collaborators to advance the state of the art of Algorithmic Game Theory and open new venues of research at the interface of Computer Science, Game Theory, and Economics. The proposal consists mainly of three intertwined research strands: algorithmic mechanism design, price of anarchy, and online algorithms.
Specifically, we will attempt to resolve some outstanding open problems in algorithmic mechanism design: characterizing the incentive compatible mechanisms for important domains, such as the domain of combinatorial auctions, and resolving the approximation ratio of mechanisms for scheduling unrelated machines. More generally, we will study centralized and distributed algorithms whose inputs are controlled by selfish agents that are interested in the outcome of the computation. We will investigate new notions of mechanisms with strong truthfulness and limited susceptibility to externalities that can facilitate modular design of mechanisms of complex domains.
We will expand the current research on the price of anarchy to time-dependent games where the players can select not only how to act but also when to act. We also plan to resolve outstanding questions on the price of stability and to build a robust approach to these questions, similar to smooth analysis. For repeated games, we will investigate convergence of simple strategies (e.g., fictitious play), online fairness, and strategic considerations (e.g., metagames). More generally, our aim is to find a productive formulation of playing unknown games by drawing on the fields of online algorithms and machine learning.
Summary
The objective of this proposal is to bring together a local team of young researchers who will work closely with international collaborators to advance the state of the art of Algorithmic Game Theory and open new venues of research at the interface of Computer Science, Game Theory, and Economics. The proposal consists mainly of three intertwined research strands: algorithmic mechanism design, price of anarchy, and online algorithms.
Specifically, we will attempt to resolve some outstanding open problems in algorithmic mechanism design: characterizing the incentive compatible mechanisms for important domains, such as the domain of combinatorial auctions, and resolving the approximation ratio of mechanisms for scheduling unrelated machines. More generally, we will study centralized and distributed algorithms whose inputs are controlled by selfish agents that are interested in the outcome of the computation. We will investigate new notions of mechanisms with strong truthfulness and limited susceptibility to externalities that can facilitate modular design of mechanisms of complex domains.
We will expand the current research on the price of anarchy to time-dependent games where the players can select not only how to act but also when to act. We also plan to resolve outstanding questions on the price of stability and to build a robust approach to these questions, similar to smooth analysis. For repeated games, we will investigate convergence of simple strategies (e.g., fictitious play), online fairness, and strategic considerations (e.g., metagames). More generally, our aim is to find a productive formulation of playing unknown games by drawing on the fields of online algorithms and machine learning.
Max ERC Funding
2 461 000 €
Duration
Start date: 2013-04-01, End date: 2019-03-31
Project acronym AlgoRNN
Project Recurrent Neural Networks and Related Machines That Learn Algorithms
Researcher (PI) Juergen Schmidhuber
Host Institution (HI) UNIVERSITA DELLA SVIZZERA ITALIANA
Country Switzerland
Call Details Advanced Grant (AdG), PE6, ERC-2016-ADG
Summary Recurrent neural networks (RNNs) are general parallel-sequential computers. Some learn their programs or weights. Our supervised Long Short-Term Memory (LSTM) RNNs were the first to win pattern recognition contests, and recently enabled best known results in speech and handwriting recognition, machine translation, etc. They are now available to billions of users through the world's most valuable public companies including Google and Apple. Nevertheless, in lots of real-world tasks RNNs do not yet live up to their full potential. Although universal in theory, in practice they fail to learn important types of algorithms. This ERC project will go far beyond today's best RNNs through novel RNN-like systems that address some of the biggest open RNN problems and hottest RNN research topics: (1) How can RNNs learn to control (through internal spotlights of attention) separate large short-memory structures such as sub-networks with fast weights, to improve performance on many natural short-term memory-intensive tasks which are currently hard to learn by RNNs, such as answering detailed questions on recently observed videos? (2) How can such RNN-like systems metalearn entire learning algorithms that outperform the original learning algorithms? (3) How to achieve efficient transfer learning from one RNN-learned set of problem-solving programs to new RNN programs solving new tasks? In other words, how can one RNN-like system actively learn to exploit algorithmic information contained in the programs running on another? We will test our systems existing benchmarks, and create new, more challenging multi-task benchmarks. This will be supported by a rather cheap, GPU-based mini-brain for implementing large RNNs.
Summary
Recurrent neural networks (RNNs) are general parallel-sequential computers. Some learn their programs or weights. Our supervised Long Short-Term Memory (LSTM) RNNs were the first to win pattern recognition contests, and recently enabled best known results in speech and handwriting recognition, machine translation, etc. They are now available to billions of users through the world's most valuable public companies including Google and Apple. Nevertheless, in lots of real-world tasks RNNs do not yet live up to their full potential. Although universal in theory, in practice they fail to learn important types of algorithms. This ERC project will go far beyond today's best RNNs through novel RNN-like systems that address some of the biggest open RNN problems and hottest RNN research topics: (1) How can RNNs learn to control (through internal spotlights of attention) separate large short-memory structures such as sub-networks with fast weights, to improve performance on many natural short-term memory-intensive tasks which are currently hard to learn by RNNs, such as answering detailed questions on recently observed videos? (2) How can such RNN-like systems metalearn entire learning algorithms that outperform the original learning algorithms? (3) How to achieve efficient transfer learning from one RNN-learned set of problem-solving programs to new RNN programs solving new tasks? In other words, how can one RNN-like system actively learn to exploit algorithmic information contained in the programs running on another? We will test our systems existing benchmarks, and create new, more challenging multi-task benchmarks. This will be supported by a rather cheap, GPU-based mini-brain for implementing large RNNs.
Max ERC Funding
2 500 000 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym ALGSTRONGCRYPTO
Project Algebraic Methods for Stronger Crypto
Researcher (PI) Ronald John Fitzgerald CRAMER
Host Institution (HI) STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN
Country Netherlands
Call Details Advanced Grant (AdG), PE6, ERC-2016-ADG
Summary Our field is cryptology. Our overarching objective is to advance significantly the frontiers in
design and analysis of high-security cryptography for the future generation.
Particularly, we wish to enhance the efficiency, functionality, and, last-but-not-least, fundamental understanding of cryptographic security against very powerful adversaries.
Our approach here is to develop completely novel methods by
deepening, strengthening and broadening the
algebraic foundations of the field.
Concretely, our lens builds on
the arithmetic codex. This is a general, abstract cryptographic primitive whose basic theory we recently developed and whose asymptotic part, which relies on algebraic geometry, enjoys crucial applications in surprising foundational results on constant communication-rate two-party cryptography. A codex is a linear (error correcting) code that, when endowing its ambient vector space just with coordinate-wise multiplication, can be viewed as simulating, up to some degree, richer arithmetical structures such as finite fields (or products thereof), or generally, finite-dimensional algebras over finite fields. Besides this degree, coordinate-localities for which simulation holds and for which it does not at all are also captured.
Our method is based on novel perspectives on codices which significantly
widen their scope and strengthen their utility. Particularly, we bring
symmetries, computational- and complexity theoretic aspects, and connections with algebraic number theory, -geometry, and -combinatorics into play in novel ways. Our applications range from public-key cryptography to secure multi-party computation.
Our proposal is subdivided into 3 interconnected modules:
(1) Algebraic- and Number Theoretical Cryptanalysis
(2) Construction of Algebraic Crypto Primitives
(3) Advanced Theory of Arithmetic Codices
Summary
Our field is cryptology. Our overarching objective is to advance significantly the frontiers in
design and analysis of high-security cryptography for the future generation.
Particularly, we wish to enhance the efficiency, functionality, and, last-but-not-least, fundamental understanding of cryptographic security against very powerful adversaries.
Our approach here is to develop completely novel methods by
deepening, strengthening and broadening the
algebraic foundations of the field.
Concretely, our lens builds on
the arithmetic codex. This is a general, abstract cryptographic primitive whose basic theory we recently developed and whose asymptotic part, which relies on algebraic geometry, enjoys crucial applications in surprising foundational results on constant communication-rate two-party cryptography. A codex is a linear (error correcting) code that, when endowing its ambient vector space just with coordinate-wise multiplication, can be viewed as simulating, up to some degree, richer arithmetical structures such as finite fields (or products thereof), or generally, finite-dimensional algebras over finite fields. Besides this degree, coordinate-localities for which simulation holds and for which it does not at all are also captured.
Our method is based on novel perspectives on codices which significantly
widen their scope and strengthen their utility. Particularly, we bring
symmetries, computational- and complexity theoretic aspects, and connections with algebraic number theory, -geometry, and -combinatorics into play in novel ways. Our applications range from public-key cryptography to secure multi-party computation.
Our proposal is subdivided into 3 interconnected modules:
(1) Algebraic- and Number Theoretical Cryptanalysis
(2) Construction of Algebraic Crypto Primitives
(3) Advanced Theory of Arithmetic Codices
Max ERC Funding
2 447 439 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym ALKAGE
Project Algebraic and Kähler geometry
Researcher (PI) Jean-Pierre, Raymond, Philippe Demailly
Host Institution (HI) UNIVERSITE GRENOBLE ALPES
Country France
Call Details Advanced Grant (AdG), PE1, ERC-2014-ADG
Summary The purpose of this project is to study basic questions in algebraic and Kähler geometry. It is well known that the structure of projective or Kähler manifolds is governed by positivity or negativity properties of the curvature tensor. However, many fundamental problems are still wide open. Since the mid 1980's, I have developed a large number of key concepts and results that have led to important progress in transcendental algebraic geometry. Let me mention the discovery of holomorphic Morse inequalities, systematic applications of L² estimates with singular hermitian metrics, and a much improved understanding of Monge-Ampère equations and of singularities of plurisuharmonic functions. My first goal will be to investigate the Green-Griffiths-Lang conjecture asserting that an entire curve drawn in a variety of general type is algebraically degenerate. The subject is intimately related to important questions concerning Diophantine equations, especially higher dimensional generalizations of Faltings' theorem - the so-called Vojta program. One can rely here on a breakthrough I made in 2010, showing that all such entire curves must satisfy algebraic differential equations. A second closely related area of research of this project is the analysis of the structure of projective or compact Kähler manifolds. It can be seen as a generalization of the classification theory of surfaces by Kodaira, and of the more recent results for dimension 3 (Kawamata, Kollár, Mori, Shokurov, ...) to other dimensions. My plan is to combine powerful recent results obtained on the duality of positive cohomology cones with an analysis of the instability of the tangent bundle, i.e. of the Harder-Narasimhan filtration. On these ground-breaking questions, I intend to go much further and to enhance my national and international collaborations. These subjects already attract many young researchers and postdocs throughout the world, and the grant could be used to create even stronger interactions.
Summary
The purpose of this project is to study basic questions in algebraic and Kähler geometry. It is well known that the structure of projective or Kähler manifolds is governed by positivity or negativity properties of the curvature tensor. However, many fundamental problems are still wide open. Since the mid 1980's, I have developed a large number of key concepts and results that have led to important progress in transcendental algebraic geometry. Let me mention the discovery of holomorphic Morse inequalities, systematic applications of L² estimates with singular hermitian metrics, and a much improved understanding of Monge-Ampère equations and of singularities of plurisuharmonic functions. My first goal will be to investigate the Green-Griffiths-Lang conjecture asserting that an entire curve drawn in a variety of general type is algebraically degenerate. The subject is intimately related to important questions concerning Diophantine equations, especially higher dimensional generalizations of Faltings' theorem - the so-called Vojta program. One can rely here on a breakthrough I made in 2010, showing that all such entire curves must satisfy algebraic differential equations. A second closely related area of research of this project is the analysis of the structure of projective or compact Kähler manifolds. It can be seen as a generalization of the classification theory of surfaces by Kodaira, and of the more recent results for dimension 3 (Kawamata, Kollár, Mori, Shokurov, ...) to other dimensions. My plan is to combine powerful recent results obtained on the duality of positive cohomology cones with an analysis of the instability of the tangent bundle, i.e. of the Harder-Narasimhan filtration. On these ground-breaking questions, I intend to go much further and to enhance my national and international collaborations. These subjects already attract many young researchers and postdocs throughout the world, and the grant could be used to create even stronger interactions.
Max ERC Funding
1 809 345 €
Duration
Start date: 2015-09-01, End date: 2021-08-31
Project acronym ALLEGRO
Project Active large-scale learning for visual recognition
Researcher (PI) Cordelia Schmid
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Country France
Call Details Advanced Grant (AdG), PE6, ERC-2012-ADG_20120216
Summary A massive and ever growing amount of digital image and video content
is available today, on sites such as
Flickr and YouTube, in audiovisual archives such as those of BBC and
INA, and in personal collections. In most cases, it comes with
additional information, such as text, audio or other metadata, that forms a
rather sparse and noisy, yet rich and diverse source of annotation,
ideally suited to emerging weakly supervised and active machine
learning technology. The ALLEGRO project will take visual recognition
to the next level by using this largely untapped source of data to
automatically learn visual models. The main research objective of
our project is the development of new algorithms and computer software
capable of autonomously exploring evolving data collections, selecting
the relevant information, and determining the visual models most
appropriate for different object, scene, and activity categories. An
emphasis will be put on learning visual models from video, a
particularly rich source of information, and on the representation of
human activities, one of today's most challenging problems in computer
vision. Although this project addresses fundamental research
issues, it is expected to result in significant advances in
high-impact applications that range from visual mining of the Web and
automated annotation and organization of family photo and video albums
to large-scale information retrieval in television archives.
Summary
A massive and ever growing amount of digital image and video content
is available today, on sites such as
Flickr and YouTube, in audiovisual archives such as those of BBC and
INA, and in personal collections. In most cases, it comes with
additional information, such as text, audio or other metadata, that forms a
rather sparse and noisy, yet rich and diverse source of annotation,
ideally suited to emerging weakly supervised and active machine
learning technology. The ALLEGRO project will take visual recognition
to the next level by using this largely untapped source of data to
automatically learn visual models. The main research objective of
our project is the development of new algorithms and computer software
capable of autonomously exploring evolving data collections, selecting
the relevant information, and determining the visual models most
appropriate for different object, scene, and activity categories. An
emphasis will be put on learning visual models from video, a
particularly rich source of information, and on the representation of
human activities, one of today's most challenging problems in computer
vision. Although this project addresses fundamental research
issues, it is expected to result in significant advances in
high-impact applications that range from visual mining of the Web and
automated annotation and organization of family photo and video albums
to large-scale information retrieval in television archives.
Max ERC Funding
2 493 322 €
Duration
Start date: 2013-04-01, End date: 2019-03-31