Samet Oymak

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Babak HassibiMose and Lilian S. Bohn Professor of Electrical EngineeringE-mail confirmado em caltech.edu
Christos ThrampoulidisAssistant Professor, University of British Columbia, ECE DepartmentE-mail confirmado em ucsb.edu
Mahdi SoltanolkotabiUniversity of Southern CaliforniaE-mail confirmado em usc.edu
Maryam FazelMoorthy Family Professor of Electrical and Computer Engineering, University of WashingtonE-mail confirmado em uw.edu
Necmiye OzayEECS, University of MichiganE-mail confirmado em umich.edu
Kishore JaganathanIllumina Artificial Intelligence LaboratoryE-mail confirmado em caltech.edu
Jiasi ChenUniversity of MichiganE-mail confirmado em umich.edu
Dimitris PapailiopoulosResearcher at Microsoft Research & Assoc. Professor at University of WisconsinE-mail confirmado em papail.io
Benjamin RechtProfessor of EECS, University of California, BerkeleyE-mail confirmado em eecs.berkeley.edu
Ankit Singh RawatResearch Scientist, GoogleE-mail confirmado em google.com
Amin khajehnejadResearchE-mail confirmado em caltech.edu
Yonina EldarMath and Computer Science, WeizmannE-mail confirmado em weizmann.ac.il
Ramya Korlakai VinayakAssistant Professor, UW-MadisonE-mail confirmado em ece.wisc.edu
Joel A. TroppSteele Family Professor of Applied & Computational Mathematics, CaltechE-mail confirmado em caltech.edu
Karthik MohanAffiliate Professor, University of Washington Seattle. Research Scientist, Facebook, RedmondE-mail confirmado em uw.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyE-mail confirmado em cs.berkeley.edu
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyE-mail confirmado em eecs.berkeley.edu
Ananda Theertha SureshGoogle Research, New YorkE-mail confirmado em google.com
Mehrdad MahdaviAssociate Professor of Computer Science, Pennsylvania State UniversityE-mail confirmado em psu.edu
Athina PetropuluECE RutgersE-mail confirmado em rutgers.edu

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Samet Oymak

EECS Prof @ University of Michigan

E-mail confirmado em umich.edu - Página inicial

machine learning statistics optimization language models


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Gradient descent with early stopping is provably robust to label noise for overparameterized neural networks M Li, M Soltanolkotabi, S Oymak AISTATS, 2020	414	2020
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks S Oymak, M Soltanolkotabi IEEE Journal on Selected Areas in Information Theory, 2020	376	2020
Simultaneously structured models with application to sparse and low-rank matrices S Oymak, A Jalali, M Fazel, YC Eldar, B Hassibi IEEE Transactions on Information Theory, 2015	316	2015
Non-asymptotic identification of LTI systems from a single trajectory S Oymak, N Ozay IEEE ACC, 2019	262	2019
Regularized linear regression: A precise analysis of the estimation error C Thrampoulidis, S Oymak, B Hassibi COLT, 2015	262*	2015
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? S Oymak, M Soltanolkotabi ICML, 2019	213	2019
Unsupervised Multi-source Domain Adaptation Without Access to Source Data SM Ahmed, DS Raychaudhuri, S Paul, S Oymak, AK Roy-Chowdhury CVPR, 2021	177	2021
Recovery of sparse 1-D signals from the magnitudes of their Fourier transform K Jaganathan, S Oymak, B Hassibi IEEE ISIT, 2012	162	2012
The squared-error of generalized lasso: A precise analysis S Oymak, C Thrampoulidis, B Hassibi 51st Annual Allerton Conference on Communication, Control, and Computing …, 2013	154	2013
Transformers as Algorithms: Generalization and Stability in In-context Learning Y Li, ME Ildiz, D Papailiopoulos, S Oymak ICML, 2023	149*	2023
Universality laws for randomized dimension reduction, with applications S Oymak, JA Tropp Information and Inference: A Journal of the IMA 7 (3), 337-446, 2018	147	2018
Sparse phase retrieval: Convex algorithms and limitations K Jaganathan, S Oymak, B Hassibi IEEE ISIT, 2013	135	2013
Sharp Time--Data Tradeoffs for Linear Inverse Problems S Oymak, B Recht, M Soltanolkotabi IEEE Transactions on Information Theory, 2018	115	2018
A simplified approach to recovery conditions for low rank matrices S Oymak, K Mohan, M Fazel, B Hassibi IEEE ISIT, 2011	112	2011
Parallel correlation clustering on big graphs X Pan, D Papailiopoulos, S Oymak, B Recht, K Ramchandran, MI Jordan NeurIPS, 2015	109	2015
New null space results and recovery thresholds for matrix rank minimization S Oymak, B Hassibi arXiv:1011.6326, 2010	107*	2010
Sharp MSE Bounds for Proximal Denoising S Oymak, B Hassibi Foundations of Computational Mathematics, 2013	105	2013
Label-Imbalanced and Group-Sensitive Classification under Overparameterization GR Kini, O Paraskevas, S Oymak, C Thrampoulidis NeurIPS, 2021	95	2021
Sparse phase retrieval: Uniqueness guarantees and recovery algorithms K Jaganathan, S Oymak, B Hassibi IEEE Transactions on Signal Processing, 2017	88	2017
Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian S Oymak, Z Fabian, M Li, M Soltanolkotabi ICML Workshop on Understanding and Improving Generalization in Deep Learning, 2019	87	2019

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