Guy Bresler

Orcid: 0000-0003-1303-582X

According to our database1, Guy Bresler authored at least 65 papers between 2006 and 2024.

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Bibliography

2024
Threshold for detecting high dimensional geometry in anisotropic random geometric graphs.
Random Struct. Algorithms, January, 2024

Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and Enumeration.
CoRR, 2024

Efficient reductions between some statistical models.
CoRR, 2024

On the Fourier Coefficients of High-Dimensional Random Geometric Graphs.
Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024

Thresholds for Reconstruction of Random Hypergraphs From Graph Projections.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Detection of L<sub>∞</sub> Geometry in Random Geometric Graphs: Suboptimality of Triangles and Cluster Expansion.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
Random Algebraic Graphs and Their Convergence to Erdos-Renyi.
CoRR, 2023

Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra Triangles.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures.
J. Mach. Learn. Res., 2022

Linear Programs with Polynomial Coefficients and Applications to 1D Cellular Automata.
CoRR, 2022

2021
Information Storage in the Stochastic Ising Model.
IEEE Trans. Inf. Theory, 2021

Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering.
IEEE Trans. Inf. Theory, 2021

De Finetti-Style Results for Wishart Matrices: Combinatorial Structure and Phase Transitions.
CoRR, 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

The Algorithmic Phase Transition of Random k-SAT for Low Degree Polynomials.
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models.
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent.
Proceedings of the Conference on Learning Theory, 2021

2020
Editorial.
IEEE J. Sel. Areas Inf. Theory, 2020

Learning Restricted Boltzmann Machines with Few Latent Variables.
CoRR, 2020

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Restricted Boltzmann Machines with Sparse Latent Variables.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Minimax Prediction in Tree Ising Models.
Proceedings of the IEEE International Symposium on Information Theory, 2020

A Corrective View of Neural Networks: Representation, Memorization and Learning.
Proceedings of the Conference on Learning Theory, 2020

Reducibility and Statistical-Computational Gaps from Secret Leakage.
Proceedings of the Conference on Learning Theory, 2020

2019
Phase Transitions for Detecting Latent Geometry in Random Graphs.
CoRR, 2019

Average-Case Lower Bounds for Learning Sparse Mixtures, Robust Estimation and Semirandom Adversaries.
CoRR, 2019

Learning restricted Boltzmann machines via influence maximization.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Sample Efficient Active Learning of Causal Trees.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Information Storage in the Stochastic Ising Model at Low Temperature.
Proceedings of the IEEE International Symposium on Information Theory, 2019

The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs.
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

Universality of Computational Lower Bounds for Submatrix Detection.
Proceedings of the Conference on Learning Theory, 2019

Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness.
Proceedings of the Conference on Learning Theory, 2019

2018
Learning Graphical Models From the Glauber Dynamics.
IEEE Trans. Inf. Theory, 2018

Learning Restricted Boltzmann Machines via Influence Maximization.
CoRR, 2018

Sparse PCA from Sparse Linear Regression.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Information Storage in the Stochastic Ising Model at Zero Temperature.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Optimal Single Sample Tests for Structured versus Unstructured Network Data.
Proceedings of the Conference On Learning Theory, 2018

Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure.
Proceedings of the Conference On Learning Theory, 2018

2016
Learning a Tree-Structured Ising Model in Order to Make Predictions.
CoRR, 2016

Collaborative Filtering with Low Regret.
Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, 2016

2015
Efficiently Learning Ising Models on Arbitrary Graphs.
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Inferning trees.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2014
Feasibility of Interference Alignment for the MIMO Interference Channel.
IEEE Trans. Inf. Theory, 2014

Efficiently learning Ising models on high degree graphs.
CoRR, 2014

Structure learning of antiferromagnetic Ising models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Hardness of parameter estimation in graphical models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A Latent Source Model for Online Collaborative Filtering.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Information Theory of DNA Shotgun Sequencing.
IEEE Trans. Inf. Theory, 2013

Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms.
SIAM J. Comput., 2013

Interference alignment for the MIMO interference channel
CoRR, 2013

Optimal Assembly for High Throughput Shotgun Sequencing
CoRR, 2013

2012
Fundamental limits and insights: from wireless communication to DNA sequencing.
PhD thesis, 2012

Information Theory of DNA Sequencing
CoRR, 2012

Information theory for DNA sequencing: Part I: A basic model.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011
Settling the feasibility of interference alignment for the MIMO interference channel: the symmetric square case
CoRR, 2011

Feasibility of interference alignment for the MIMO interference channel: The symmetric square case.
Proceedings of the 2011 IEEE Information Theory Workshop, 2011

Geometry of the 3-user MIMO interference channel.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010
The approximate capacity of the many-to-one and one-to-many Gaussian interference channels.
IEEE Trans. Inf. Theory, 2010

2009
3 User interference channel: Degrees of freedom as a function of channel diversity.
Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008
The two-user Gaussian interference channel: a deterministic view.
Eur. Trans. Telecommun., 2008

Mixing Time of Exponential Random Graphs.
Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science, 2008

2007
Reconstruction of Markov Random Fields from Samples: Some Easy Observations and Algorithms
CoRR, 2007

2006
Note On Mutual Information and Orthogonal Space-Time Codes.
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006


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