Emmanuel Abbe

Orcid: 0000-0002-8014-5706

Affiliations:
  • EPFL, Switzerland
  • Princeton University, USA (former)


According to our database1, Emmanuel Abbe authored at least 112 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

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Bibliography

2024
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization.
CoRR, 2024

Visual Scratchpads: Enabling Global Reasoning in Vision.
CoRR, 2024

How Far Can Transformers Reason? The Locality Barrier and Inductive Scratchpad.
CoRR, 2024

Graph Neural Network based Future Clinical Events Prediction from Invasive Coronary Angiography.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

When can transformers reason with abstract symbols?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Reed-Muller Codes.
Found. Trends Commun. Inf. Theory, 2023

Reed-Muller codes have vanishing bit-error probability below capacity: a simple tighter proof via camellia boosting.
CoRR, 2023

Boolformer: Symbolic Regression of Logic Functions with Transformers.
CoRR, 2023

Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Transformers learn through gradual rank increase.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalization on the Unseen, Logic Reasoning and Degree Curriculum.
Proceedings of the International Conference on Machine Learning, 2023

A proof that Reed-Muller codes achieve Shannon capacity on symmetric channels.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Can Knowledge Transfer Techniques Compensate for the Limited Myocardial Infarction Data by Leveraging Hæmodynamics? An in silico Study.
Proceedings of the Artificial Intelligence in Medicine, 2023

2022
Binary perceptron: efficient algorithms can find solutions in a rare well-connected cluster.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the non-universality of deep learning: quantifying the cost of symmetry.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn.
Proceedings of the International Conference on Machine Learning, 2022

The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Reed-Muller Codes: Theory and Algorithms.
IEEE Trans. Inf. Theory, 2021

Almost-Reed-Muller Codes Achieve Constant Rates for Random Errors.
IEEE Trans. Inf. Theory, 2021

On the Power of Differentiable Learning versus PAC and SQ Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The staircase property: How hierarchical structure can guide deep learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels.
Proceedings of the 38th International Conference on Machine Learning, 2021

Proof of the Contiguity Conjecture and Lognormal Limit for the Symmetric Perceptron.
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Stochastic block model entropy and broadcasting on trees with survey.
Proceedings of the Conference on Learning Theory, 2021

2020
Reed-Muller Codes Polarize.
IEEE Trans. Inf. Theory, 2020

Recursive Projection-Aggregation Decoding of Reed-Muller Codes.
IEEE Trans. Inf. Theory, 2020

Graph Powering and Spectral Robustness.
SIAM J. Math. Data Sci., 2020

Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks.
J. Mach. Learn. Res., 2020

Generalized Nonbacktracking Bounds on the Influence.
J. Mach. Learn. Res., 2020

Maximum Multiscale Entropy and Neural Network Regularization.
CoRR, 2020

An 𝓁<sub>p</sub> theory of PCA and spectral clustering.
CoRR, 2020

An Alon-Boppana theorem for powered graphs and generalized Ramanujan graphs.
CoRR, 2020

Learning Sparse Graphons and the Generalized Kesten-Stigum Threshold.
CoRR, 2020

Poly-time universality and limitations of deep learning.
CoRR, 2020

On the universality of deep learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Polarization in Attraction-Repulsion Models.
Proceedings of the IEEE International Symposium on Information Theory, 2020

2019
Multireference Alignment Is Easier With an Aperiodic Translation Distribution.
IEEE Trans. Inf. Theory, 2019

Entropic Matroids and Their Representation.
Entropy, 2019

Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets.
CoRR, 2019

Subadditivity Beyond Trees and the Chi-Squared Mutual Information.
Proceedings of the IEEE International Symposium on Information Theory, 2019

2018
Community Detection and Stochastic Block Models.
Found. Trends Commun. Inf. Theory, 2018

Provable limitations of deep learning.
CoRR, 2018

An Information-Percolation Bound for Spin Synchronization on General Graphs.
CoRR, 2018

Chaining Mutual Information and Tightening Generalization Bounds.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Estimation in the Group Action Channel.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Communication-Computation Efficient Gradient Coding.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Polarization of the Rényi Information Dimension With Applications to Compressed Sensing.
IEEE Trans. Inf. Theory, 2017

Learning from graphical data.
SIGMETRICS Perform. Evaluation Rev., 2017

Community Detection and Stochastic Block Models: Recent Developments.
J. Mach. Learn. Res., 2017

Entropies of Weighted Sums in Cyclic Groups and an Application to Polar Codes.
Entropy, 2017

Multireference Alignment is Easier with an Aperiodic Translation Distribution.
CoRR, 2017

Group Synchronization on Grids.
CoRR, 2017

Nonbacktracking Bounds on the Influence in Independent Cascade Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Compressing data on graphs with clusters.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Sample complexity of the boolean multireference alignment problem.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016
Exact Recovery in the Stochastic Block Model.
IEEE Trans. Inf. Theory, 2016

Linear Boolean Classification, Coding and the Critical Problem.
IEEE Trans. Inf. Theory, 2016

Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Asymptotic mutual information for the binary stochastic block model.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Crossing the KS threshold in the stochastic block model with information theory.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Spectral bounds for independent cascade model with sensitive edges.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Detecting community structures in Hi-C genomic data.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Graph compression: The effect of clusters.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015
Conditional Random Fields, Planted Constraint Satisfaction, and Entropy Concentration.
Theory Comput., 2015

Polar Codes for Broadcast Channels.
IEEE Trans. Inf. Theory, 2015

Polar Coding for Secret-Key Generation.
IEEE Trans. Inf. Theory, 2015

Reed-Muller Codes for Random Erasures and Errors.
IEEE Trans. Inf. Theory, 2015

Randomness and Dependencies Extraction via Polarization, With Applications to Slepian-Wolf Coding and Secrecy.
IEEE Trans. Inf. Theory, 2015

Statistical ADC Enhanced by Pipelining and Subranging.
IEEE Trans. Circuits Syst. II Express Briefs, 2015

Asymptotic Mutual Information for the Two-Groups Stochastic Block Model.
CoRR, 2015

Detection in the stochastic block model with multiple clusters: proof of the achievability conjectures, acyclic BP, and the information-computation gap.
CoRR, 2015

Community detection in general stochastic block models: fundamental limits and efficient recovery algorithms.
CoRR, 2015

Entropies of weighted sums in cyclic groups and applications to polar codes.
CoRR, 2015

Concentration of the number of solutions of random planted CSPs and Goldreich's one-way candidates.
CoRR, 2015

Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

High-Girth matrices and polarization.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Community Detection in General Stochastic Block models: Fundamental Limits and Efficient Algorithms for Recovery.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2014
Decoding Binary Node Labels from Censored Edge Measurements: Phase Transition and Efficient Recovery.
IEEE Trans. Netw. Sci. Eng., 2014

A New Entropy Power Inequality for Integer-Valued Random Variables.
IEEE Trans. Inf. Theory, 2014

On the concentration of the number of solutions of random satisfiability formulas.
Random Struct. Algorithms, 2014

A Shannon Approach to Secure Multi-party Computations.
CoRR, 2014

Linear inverse problems on Erdős-Rényi graphs: Information-theoretic limits and efficient recovery.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Linear Boolean classification, coding and "the critical problem".
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Polynomial complexity of polar codes for non-binary alphabets, key agreement and Slepian-Wolf coding.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

Two shannon-type problems on secure multi-party computations.
Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

2013
Proof of the Outage Probability Conjecture for MISO Channels.
IEEE Trans. Inf. Theory, 2013

Conditional Random Fields, Planted Satisfaction, and Entropy Concentration
CoRR, 2013

Polarization of the Rényi information dimension for single and multi terminal analog compression.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

The mutual information of a class of graphical channels.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
A Coordinate System for Gaussian Networks.
IEEE Trans. Inf. Theory, 2012

Polar Codes for the m-User Multiple Access Channel.
IEEE Trans. Inf. Theory, 2012

Adaptive sensing using deterministic partial Hadamard matrices.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011
Privacy-Preserving Methods for Sharing Financial Risk Exposures
CoRR, 2011

Extracting randomness and dependencies via a matrix polarization
CoRR, 2011

Randomness and dependencies extraction via polarization.
Proceedings of the Information Theory and Applications Workshop, 2011

Polar coding in networks: Known results and new directions.
Proceedings of the 8th International Symposium on Wireless Communication Systems, 2011

Polar coding schemes for the AWGN channel.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Polarization and randomness extraction.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

2010
Linear Universal Decoding for Compound Channels.
IEEE Trans. Inf. Theory, 2010

Mutual information, matroids and extremal dependencies
CoRR, 2010

Universal polar coding and sparse recovery
CoRR, 2010

Polar Codes for the m-User MAC and Matroids
CoRR, 2010

Universal a posteriori metrics game.
Proceedings of the 2010 IEEE Information Theory Workshop, 2010

Universal source polarization and sparse recovery.
Proceedings of the 2010 IEEE Information Theory Workshop, 2010

MAC polar codes and matroids.
Proceedings of the Information Theory and Applications Workshop, 2010

2009
Coding along Hermite polynomials for Gaussian noise channels.
Proceedings of the IEEE International Symposium on Information Theory, 2009

2008
Local to global geometric methods in information theory.
PhD thesis, 2008

Linear Universal Decoding for Compound Channels: a Local to Global Geometric Approach
CoRR, 2008

Linear universal decoding for compound channels: an Euclidean Geometric Approach.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008


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