Guy Bresler

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David TseThomas Kailath and Guanghan Xu Professor, Stanford UniversityAdresă de e-mail confirmată pe stanford.edu
Dheeraj NagarajResearch Scientist, GoogleAdresă de e-mail confirmată pe google.com
Devavrat ShahMassachusetts Institute of TechnologyAdresă de e-mail confirmată pe mit.edu
Allan SlyDepartment of Mathmatics, Princeton University Department of Statistics, University of CaliforniaAdresă de e-mail confirmată pe princeton.edu
Enric Boix-AdseràPhD Student in EECS, MITAdresă de e-mail confirmată pe mit.edu
Mina KarzandMITAdresă de e-mail confirmată pe mit.edu
David GamarnikProfessor of Operations Research, MITAdresă de e-mail confirmată pe mit.edu
Elchanan MosselProfessor of Mathematics, MITAdresă de e-mail confirmată pe mit.edu
Brice HuangGraduate student in EECS, MITAdresă de e-mail confirmată pe mit.edu
Shankar BhamidiProfessor, University of North Carolina, Chapel HillAdresă de e-mail confirmată pe email.unc.edu
Frederic KoehlerUniversity of ChicagoAdresă de e-mail confirmată pe uchicago.edu
George H. ChenAssociate Professor, Carnegie Mellon UniversityAdresă de e-mail confirmată pe cmu.edu
Praneeth NetrapalliGoogle ResearchAdresă de e-mail confirmată pe google.com
Prateek JainGoogle Research IndiaAdresă de e-mail confirmată pe google.com
Samuel B. HopkinsMassachusetts Institute of TechnologyAdresă de e-mail confirmată pe mit.edu
Jerry LiUniversity of WashingtonAdresă de e-mail confirmată pe cs.washington.edu
Tselil SchrammStanford UniversityAdresă de e-mail confirmată pe stanford.edu
Emmanuel AbbeProfessor EPFL, Senior Research Scientist AppleAdresă de e-mail confirmată pe epfl.ch
Chenghao GuoMassachusetts Institute of TechnologyAdresă de e-mail confirmată pe mit.edu
Ankur MoitraNorbert Wiener Professor of Mathematics, MITAdresă de e-mail confirmată pe mit.edu

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Guy Bresler

MIT

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Information theory statistics probability


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
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	378	2010
The two‐user Gaussian interference channel: a deterministic view G Bresler, D Tse European transactions on telecommunications 19 (4), 333-354, 2008	270	2008
Efficiently learning Ising models on arbitrary graphs G Bresler Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015	235	2015
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	226*	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	212	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	184*	2013
Information Theory of DNA Shotgun Sequencing A Motahari, G Bresler, D Tse IEEE Transactions on Information Theory, 1-1, 2013	153	2013
Reducibility and computational lower bounds for problems with planted sparse structure M Brennan, G Bresler, W Huleihel Conference On Learning Theory, 48-166, 2018	129	2018
Reducibility and statistical-computational gaps from secret leakage M Brennan, G Bresler Conference on Learning Theory, 648-847, 2020	115*	2020
The staircase property: How hierarchical structure can guide deep learning E Abbe, E Boix Adsera, M Brennan, G Bresler, D Nagaraj Advances in Neural Information Processing Systems 34, 2021	110*	2021
Optimal assembly for high throughput shotgun sequencing G Bresler, M Bresler, D Tse BMC bioinformatics 14 (5), 1-13, 2013	102	2013
A Latent Source Model for Online Collaborative Filtering G Bresler, GH Chen, D Shah Advances in Neural Information Processing Systems, 3347-3355, 2014	87	2014
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms D Nagaraj, X Wu, G Bresler, P Jain, P Netrapalli Advances in Neural Information Processing Systems 33, 2020	80	2020
Statistical query algorithms and low-degree tests are almost equivalent M Brennan, G Bresler, SB Hopkins, J Li, T Schramm Conference on Learning Theory, 2021	78	2021
Optimal average-case reductions to sparse pca: From weak assumptions to strong hardness M Brennan, G Bresler Conference on Learning Theory, 469-470, 2019	68	2019
Learning a tree-structured Ising model in order to make predictions G Bresler, M Karzand The Annals of Statistics 48 (2), 713-737, 2020	61	2020
The algorithmic phase transition of random k-sat for low degree polynomials G Bresler, B Huang 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022	56	2022
The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs E Boix-Adserà, M Brennan, G Bresler 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS …, 2019	52	2019
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	52*	2009
Sample Efficient Active Learning of Causal Trees K Greenewald, D Katz, K Shanmugam, S Magliacane, M Kocaoglu, ... Advances in Neural Information Processing Systems, 14279-14289, 2019	47	2019

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