Guy Bresler
Guy Bresler
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Cited by
Cited by
The approximate capacity of the many-to-one and one-to-many Gaussian interference channels
G Bresler, A Parekh, DNC Tse
Information Theory, IEEE Transactions on 56 (9), 4566-4592, 2010
The two‐user Gaussian interference channel: a deterministic view
G Bresler, D Tse
European transactions on telecommunications 19 (4), 333-354, 2008
Feasibility of Interference Alignment for the MIMO Interference Channel
G Bresler, D Cartwright, D Tse
Information Theory, IEEE Transactions on 60 (9), 5573-5586, 2014
Mixing time of exponential random graphs
S Bhamidi, G Bresler, A Sly
2008 49th Annual IEEE Symposium on Foundations of Computer Science, 803-812, 2008
Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms
G Bresler, E Mossel, A Sly
SIAM Journal on Computing 42 (2), 563-578, 2013
Efficiently learning Ising models on arbitrary graphs
G Bresler
Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015
Information Theory of DNA Shotgun Sequencing
A Motahari, G Bresler, D Tse
IEEE Transactions on Information Theory, 1-1, 2013
Optimal assembly for high throughput shotgun sequencing
G Bresler, M Bresler, D Tse
BMC bioinformatics 14 (5), S18, 2013
A Latent Source Model for Online Collaborative Filtering
G Bresler, GH Chen, D Shah
Advances in Neural Information Processing Systems, 3347-3355, 2014
3 user interference channel: Degrees of freedom as a function of channel diversity
G Bresler, DNC Tse
Communication, Control, and Computing, 2009. Allerton 2009. 47th Annual …, 2009
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure
M Brennan, G Bresler, W Huleihel
arXiv preprint arXiv:1806.07508, 2018
Structure learning of antiferromagnetic Ising models
G Bresler, D Gamarnik, D Shah
Advances in Neural Information Processing Systems, 2852-2860, 2014
Hardness of parameter estimation in graphical models
G Bresler, D Gamarnik, D Shah
Advances in Neural Information Processing Systems, 1062-1070, 2014
Collaborative filtering with low regret
G Bresler, D Shah, LF Voloch
ACM SIGMETRICS Performance Evaluation Review 44 (1), 207-220, 2016
Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness
M Brennan, G Bresler
arXiv preprint arXiv:1902.07380, 2019
Learning a Tree-Structured Ising Model in Order to Make Predictions
G Bresler, M Karzand
arXiv preprint arXiv:1604.06749, 2016
Universality of Computational Lower Bounds for Submatrix Detection
M Brennan, G Bresler, W Huleihel
arXiv preprint arXiv:1902.06916, 2019
Optimal Single Sample Tests for Structured versus Unstructured Network Data
G Bresler, D Nagaraj
arXiv preprint arXiv:1802.06186, 2018
Learning restricted Boltzmann machines via influence maximization
G Bresler, F Koehler, A Moitra
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019
Note on mutual information and orthogonal space-time codes
G Bresler, B Hajek
2006 IEEE International Symposium on Information Theory, 1315-1318, 2006
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