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2020 – today
- 2024
[j11]Matthew S. Brennan, Guy Bresler, Brice Huang:
Threshold for detecting high dimensional geometry in anisotropic random geometric graphs. Random Struct. Algorithms 64(1): 125-137 (2024)- [c40]Kiril Bangachev, Guy Bresler:
Detection of L∞ Geometry in Random Geometric Graphs: Suboptimality of Triangles and Cluster Expansion. COLT 2024: 427-497 - [c39]Guy Bresler, Chenghao Guo, Yury Polyanskiy:
Thresholds for Reconstruction of Random Hypergraphs From Graph Projections. COLT 2024: 632-647 - [c38]Kiril Bangachev
, Guy Bresler:
On the Fourier Coefficients of High-Dimensional Random Geometric Graphs. STOC 2024: 549-560 - [i45]Mengqi Lou, Guy Bresler, Ashwin Pananjady:
Efficient reductions between some statistical models. CoRR abs/2402.07717 (2024) - [i44]Kiril Bangachev, Guy Bresler:
On The Fourier Coefficients of High-Dimensional Random Geometric Graphs. CoRR abs/2402.12589 (2024) - [i43]Kiril Bangachev, Guy Bresler:
Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and Enumeration. CoRR abs/2408.00995 (2024) - 2023
- [c37]Guy Bresler, Tianze Jiang:
Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique. COLT 2023: 5850-5889 - [c36]Guy Bresler, Chenghao Guo, Yury Polyanskiy:
Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra Triangles. FOCS 2023: 2149-2158 - [i42]Kiril Bangachev, Guy Bresler:
Random Algebraic Graphs and Their Convergence to Erdos-Renyi. CoRR abs/2305.04802 (2023) - [i41]Guy Bresler, Chenghao Guo, Yury Polyanskiy:
Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra Triangles. CoRR abs/2305.09995 (2023) - [i40]Guy Bresler, Tianze Jiang:
Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique. CoRR abs/2306.17719 (2023) - 2022
- [j10]Nir Weinberger, Guy Bresler:
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures. J. Mach. Learn. Res. 23: 103:1-103:79 (2022) - [i39]Guy Bresler, Chenghao Guo, Yury Polyanskiy:
Linear Programs with Polynomial Coefficients and Applications to 1D Cellular Automata. CoRR abs/2204.06357 (2022) - [i38]Matthew S. Brennan, Guy Bresler, Brice Huang:
Threshold for Detecting High Dimensional Geometry in Anisotropic Random Geometric Graphs. CoRR abs/2206.14896 (2022) - 2021
- [j9]Ziv Goldfeld, Guy Bresler, Yury Polyanskiy:
Information Storage in the Stochastic Ising Model. IEEE Trans. Inf. Theory 67(3): 1373-1399 (2021) - [j8]Guy Bresler, Mina Karzand:
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering. IEEE Trans. Inf. Theory 67(6): 4197-4222 (2021) - [c35]Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm:
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. COLT 2021: 774 - [c34]Guy Bresler, Brice Huang:
The Algorithmic Phase Transition of Random k-SAT for Low Degree Polynomials. FOCS 2021: 298-309 - [c33]Enric Boix-Adserà, Guy Bresler, Frederic Koehler:
Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models. FOCS 2021: 417-426 - [c32]Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
The staircase property: How hierarchical structure can guide deep learning. NeurIPS 2021: 26989-27002 - [i37]Matthew S. Brennan, Guy Bresler, Brice Huang:
De Finetti-Style Results for Wishart Matrices: Combinatorial Structure and Phase Transitions. CoRR abs/2103.14011 (2021) - [i36]Nir Weinberger, Guy Bresler:
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures. CoRR abs/2103.15653 (2021) - [i35]Guy Bresler, Brice Huang:
The Algorithmic Phase Transition of Random k-SAT for Low Degree Polynomials. CoRR abs/2106.02129 (2021) - [i34]Enric Boix-Adserà, Guy Bresler, Frederic Koehler:
Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models. CoRR abs/2106.03969 (2021) - [i33]Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
The staircase property: How hierarchical structure can guide deep learning. CoRR abs/2108.10573 (2021) - 2020
- [j7]Devavrat Shah, Guy Bresler, John C. Duchi, Po-Ling Loh, Yihong Wu, Christina Lee Yu:
Editorial. IEEE J. Sel. Areas Inf. Theory 1(3): 612 (2020) - [c31]Matthew S. Brennan, Guy Bresler:
Reducibility and Statistical-Computational Gaps from Secret Leakage. COLT 2020: 648-847 - [c30]Guy Bresler, Dheeraj Nagaraj:
A Corrective View of Neural Networks: Representation, Memorization and Learning. COLT 2020: 848-901 - [c29]Guy Bresler, Mina Karzand:
Minimax Prediction in Tree Ising Models. ISIT 2020: 1325-1330 - [c28]Guy Bresler, Rares-Darius Buhai:
Learning Restricted Boltzmann Machines with Sparse Latent Variables. NeurIPS 2020 - [c27]Guy Bresler, Dheeraj Nagaraj:
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. NeurIPS 2020 - [c26]Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain, Praneeth Netrapalli:
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. NeurIPS 2020 - [i32]Guy Bresler, Dheeraj Nagaraj:
A Corrective View of Neural Networks: Representation, Memorization and Learning. CoRR abs/2002.00274 (2020) - [i31]Matthew S. Brennan, Guy Bresler:
Reducibility and Statistical-Computational Gaps from Secret Leakage. CoRR abs/2005.08099 (2020) - [i30]Guy Bresler, Dheeraj Nagaraj:
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. CoRR abs/2006.04048 (2020) - [i29]Guy Bresler, Rares-Darius Buhai:
Learning Restricted Boltzmann Machines with Few Latent Variables. CoRR abs/2006.04166 (2020) - [i28]Guy Bresler, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli, Xian Wu:
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. CoRR abs/2006.08916 (2020) - [i27]Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm:
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent. CoRR abs/2009.06107 (2020)
2010 – 2019
- 2019
- [c25]Matthew S. Brennan, Guy Bresler, Wasim Huleihel:
Universality of Computational Lower Bounds for Submatrix Detection. COLT 2019: 417-468 - [c24]Matthew S. Brennan, Guy Bresler:
Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness. COLT 2019: 469-470 - [c23]Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler:
The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs. FOCS 2019: 1256-1280 - [c22]Ziv Goldfeld, Guy Bresler, Yury Polyanskiy:
Information Storage in the Stochastic Ising Model at Low Temperature. ISIT 2019: 732-736 - [c21]Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler:
Sample Efficient Active Learning of Causal Trees. NeurIPS 2019: 14279-14289 - [c20]Guy Bresler, Frederic Koehler, Ankur Moitra:
Learning restricted Boltzmann machines via influence maximization. STOC 2019: 828-839 - [i26]Matthew S. Brennan, Guy Bresler, Wasim Huleihel:
Universality of Computational Lower Bounds for Submatrix Detection. CoRR abs/1902.06916 (2019) - [i25]Matthew S. Brennan, Guy Bresler:
Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness. CoRR abs/1902.07380 (2019) - [i24]Enric Boix Adserà, Matthew S. Brennan, Guy Bresler:
The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs. CoRR abs/1903.08247 (2019) - [i23]Matthew S. Brennan, Guy Bresler:
Average-Case Lower Bounds for Learning Sparse Mixtures, Robust Estimation and Semirandom Adversaries. CoRR abs/1908.06130 (2019) - [i22]Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
Phase Transitions for Detecting Latent Geometry in Random Graphs. CoRR abs/1910.14167 (2019) - 2018
- [j6]Guy Bresler, David Gamarnik, Devavrat Shah:
Learning Graphical Models From the Glauber Dynamics. IEEE Trans. Inf. Theory 64(6): 4072-4080 (2018) - [c19]Matthew S. Brennan, Guy Bresler, Wasim Huleihel:
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure. COLT 2018: 48-166 - [c18]Guy Bresler, Dheeraj Nagaraj:
Optimal Single Sample Tests for Structured versus Unstructured Network Data. COLT 2018: 1657-1690 - [c17]Ziv Goldfeld, Guy Bresler, Yury Polyanskiy:
Information Storage in the Stochastic Ising Model at Zero Temperature. ISIT 2018: 2127-2131 - [c16]Guy Bresler, Mina Karzand:
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering. ITA 2018: 1-37 - [c15]Guy Bresler, Sung Min Park, Madalina Persu:
Sparse PCA from Sparse Linear Regression. NeurIPS 2018: 10965-10975 - [i21]Guy Bresler, Dheeraj Nagaraj:
Optimal Single Sample Tests for Structured versus Unstructured Network Data. CoRR abs/1802.06186 (2018) - [i20]Ziv Goldfeld, Guy Bresler, Yury Polyanskiy:
Information Storage in the Stochastic Ising Model. CoRR abs/1805.03027 (2018) - [i19]Guy Bresler, Frederic Koehler, Ankur Moitra, Elchanan Mossel:
Learning Restricted Boltzmann Machines via Influence Maximization. CoRR abs/1805.10262 (2018) - [i18]Matthew S. Brennan, Guy Bresler, Wasim Huleihel:
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure. CoRR abs/1806.07508 (2018) - [i17]Guy Bresler, Sung Min Park, Madalina Persu:
Sparse PCA from Sparse Linear Regression. CoRR abs/1811.10106 (2018) - 2017
- [i16]Guy Bresler, Mina Karzand:
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering. CoRR abs/1711.02198 (2017) - 2016
- [c14]Guy Bresler, Devavrat Shah, Luis Filipe Voloch:
Collaborative Filtering with Low Regret. SIGMETRICS 2016: 207-220 - [i15]Guy Bresler, Mina Karzand:
Learning a Tree-Structured Ising Model in Order to Make Predictions. CoRR abs/1604.06749 (2016) - 2015
- [c13]Mina Karzand, Guy Bresler:
Inferning trees. Allerton 2015: 1344-1351 - [c12]Guy Bresler:
Efficiently Learning Ising Models on Arbitrary Graphs. STOC 2015: 771-782 - [i14]Guy Bresler, Devavrat Shah, Luis Filipe Voloch:
Collaborative Filtering with Low Regret. CoRR abs/1507.05371 (2015) - 2014
- [j5]Guy Bresler, Dustin Cartwright, David Tse:
Feasibility of Interference Alignment for the MIMO Interference Channel. IEEE Trans. Inf. Theory 60(9): 5573-5586 (2014) - [c11]Guy Bresler, David Gamarnik, Devavrat Shah:
Learning graphical models from the Glauber dynamics. Allerton 2014: 1148-1155 - [c10]Guy Bresler, David Gamarnik, Devavrat Shah:
Hardness of parameter estimation in graphical models. NIPS 2014: 1062-1070 - [c9]Guy Bresler, David Gamarnik, Devavrat Shah:
Structure learning of antiferromagnetic Ising models. NIPS 2014: 2852-2860 - [c8]Guy Bresler, George H. Chen, Devavrat Shah:
A Latent Source Model for Online Collaborative Filtering. NIPS 2014: 3347-3355 - [i13]Guy Bresler, David Gamarnik, Devavrat Shah:
Hardness of parameter estimation in graphical models. CoRR abs/1409.3836 (2014) - [i12]Guy Bresler, David Gamarnik, Devavrat Shah:
Learning graphical models from the Glauber dynamics. CoRR abs/1410.7659 (2014) - [i11]Guy Bresler:
Efficiently learning Ising models on high degree graphs. CoRR abs/1411.6156 (2014) - [i10]Guy Bresler, George H. Chen, Devavrat Shah:
A Latent Source Model for Online Collaborative Filtering. CoRR abs/1411.6591 (2014) - [i9]Guy Bresler, David Gamarnik, Devavrat Shah:
Structure learning of antiferromagnetic Ising models. CoRR abs/1412.1443 (2014) - 2013
- [j4]Guy Bresler, Elchanan Mossel, Allan Sly:
Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms. SIAM J. Comput. 42(2): 563-578 (2013) - [j3]Abolfazl S. Motahari, Guy Bresler, David N. C. Tse:
Information Theory of DNA Shotgun Sequencing. IEEE Trans. Inf. Theory 59(10): 6273-6289 (2013) - [i8]Guy Bresler, Ma'ayan Bresler, David Tse:
Optimal Assembly for High Throughput Shotgun Sequencing. CoRR abs/1301.0068 (2013) - [i7]Guy Bresler, Dustin Cartwright, David Tse:
Interference alignment for the MIMO interference channel. CoRR abs/1303.5678 (2013) - 2012
- [b1]Guy Bresler:
Fundamental limits and insights: from wireless communication to DNA sequencing. University of California, Berkeley, USA, 2012 - [c7]Abolfazl S. Motahari, Guy Bresler, David Tse:
Information theory for DNA sequencing: Part I: A basic model. ISIT 2012: 2741-2745 - [i6]Abolfazl S. Motahari, Guy Bresler, David Tse:
Information Theory of DNA Sequencing. CoRR abs/1203.6233 (2012) - 2011
- [c6]Guy Bresler, Dustin Cartwright, David Tse:
Geometry of the 3-user MIMO interference channel. Allerton 2011: 1264-1271 - [c5]Guy Bresler, Dustin Cartwright, David N. C. Tse:
Feasibility of interference alignment for the MIMO interference channel: The symmetric square case. ITW 2011: 447-451 - [i5]Guy Bresler, Dustin Cartwright, David Tse:
Settling the feasibility of interference alignment for the MIMO interference channel: the symmetric square case. CoRR abs/1104.0888 (2011) - [i4]Guy Bresler, Dustin Cartwright, David Tse:
Geometry of the 3-user MIMO interference channel. CoRR abs/1110.5092 (2011) - 2010
- [j2]Guy Bresler, Abhay Parekh, David N. C. Tse:
The approximate capacity of the many-to-one and one-to-many Gaussian interference channels. IEEE Trans. Inf. Theory 56(9): 4566-4592 (2010)
2000 – 2009
- 2009
- [c4]Guy Bresler, David N. C. Tse:
3 User interference channel: Degrees of freedom as a function of channel diversity. Allerton 2009: 265-271 - 2008
- [j1]Guy Bresler, David Tse:
The two-user Gaussian interference channel: a deterministic view. Eur. Trans. Telecommun. 19(4): 333-354 (2008) - [c3]Guy Bresler, Elchanan Mossel, Allan Sly:
Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms. APPROX-RANDOM 2008: 343-356 - [c2]Shankar Bhamidi, Guy Bresler, Allan Sly:
Mixing Time of Exponential Random Graphs. FOCS 2008: 803-812 - [i3]Guy Bresler, David Tse:
The two-user Gaussian interference channel: a deterministic view. CoRR abs/0807.3222 (2008) - [i2]Guy Bresler, Abhay Parekh, David Tse:
The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels. CoRR abs/0809.3554 (2008) - 2007
- [i1]Guy Bresler, Elchanan Mossel, Allan Sly:
Reconstruction of Markov Random Fields from Samples: Some Easy Observations and Algorithms. CoRR abs/0712.1402 (2007) - 2006
- [c1]Guy Bresler, Bruce E. Hajek:
Note On Mutual Information and Orthogonal Space-Time Codes. ISIT 2006: 1315-1318
Coauthor Index
David Tse
aka: David N. C. Tse
aka: David N. C. Tse
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last updated on 2024-09-30 00:07 CEST by the dblp team
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