Guy Bresler

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David TseThomas Kailath and Guanghan Xu Professor, Stanford UniversityEmail yang diverifikasi di stanford.edu
Dheeraj NagarajResearch Scientist, GoogleEmail yang diverifikasi di google.com
Devavrat ShahMassachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Allan SlyDepartment of Mathmatics, Princeton University Department of Statistics, University of CaliforniaEmail yang diverifikasi di princeton.edu
Enric Boix-AdseràPhD Student in EECS, MITEmail yang diverifikasi di mit.edu
Mina KarzandMITEmail yang diverifikasi di mit.edu
David GamarnikProfessor of Operations Research, MITEmail yang diverifikasi di mit.edu
Elchanan MosselProfessor of Mathematics, MITEmail yang diverifikasi di mit.edu
Brice HuangGraduate student in EECS, MITEmail yang diverifikasi di mit.edu
Shankar BhamidiProfessor, University of North Carolina, Chapel HillEmail yang diverifikasi di email.unc.edu
Frederic KoehlerUniversity of ChicagoEmail yang diverifikasi di uchicago.edu
George H. ChenAssociate Professor, Carnegie Mellon UniversityEmail yang diverifikasi di cmu.edu
Praneeth NetrapalliGoogle ResearchEmail yang diverifikasi di google.com
Prateek JainGoogle Research IndiaEmail yang diverifikasi di google.com
Samuel B. HopkinsMassachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Jerry LiUniversity of WashingtonEmail yang diverifikasi di cs.washington.edu
Tselil SchrammStanford UniversityEmail yang diverifikasi di stanford.edu
Emmanuel AbbeProfessor EPFL, Senior Research Scientist AppleEmail yang diverifikasi di epfl.ch
Chenghao GuoMassachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Ankur MoitraNorbert Wiener Professor of Mathematics, MITEmail yang diverifikasi di mit.edu

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Guy Bresler

MIT

Email yang diverifikasi di mit.edu - Beranda

Information theory statistics probability


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	213	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	130	2018
Reducibility and statistical-computational gaps from secret leakage M Brennan, G Bresler Conference on Learning Theory, 648-847, 2020	116*	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	81	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	69	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	57	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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