Samet Oymak

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Babak HassibiMose and Lilian S. Bohn Professor of Electrical EngineeringEmail verificata su caltech.edu
Christos ThrampoulidisAssistant Professor, University of British Columbia, ECE DepartmentEmail verificata su ucsb.edu
Mahdi SoltanolkotabiUniversity of Southern CaliforniaEmail verificata su usc.edu
Maryam FazelMoorthy Family Professor of Electrical and Computer Engineering, University of WashingtonEmail verificata su uw.edu
Jiasi ChenUniversity of Michigan, Ann ArborEmail verificata su umich.edu
Necmiye OzayEECS, University of MichiganEmail verificata su umich.edu
Kishore JaganathanIllumina Artificial Intelligence LaboratoryEmail verificata su caltech.edu
Dimitris PapailiopoulosResearcher at Microsoft Research & Assoc. Professor at University of WisconsinEmail verificata su papail.io
Benjamin RechtProfessor of EECS, University of California, BerkeleyEmail verificata su eecs.berkeley.edu
Ankit Singh RawatResearch Scientist, GoogleEmail verificata su google.com
Amin khajehnejadResearchEmail verificata su caltech.edu
Yonina EldarMath and Computer Science, WeizmannEmail verificata su weizmann.ac.il
Ramya Korlakai VinayakAssistant Professor, UW-MadisonEmail verificata su ece.wisc.edu
Joel A. TroppSteele Family Professor of Applied & Computational Mathematics, CaltechEmail verificata su caltech.edu
Karthik MohanAffiliate Professor, University of Washington Seattle. Research Scientist, Facebook, RedmondEmail verificata su uw.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail verificata su cs.berkeley.edu
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyEmail verificata su eecs.berkeley.edu
Ananda Theertha SureshGoogle Research, New YorkEmail verificata su google.com
Mehrdad MahdaviAssociate Professor of Computer Science, Pennsylvania State UniversityEmail verificata su psu.edu
Athina PetropuluECE RutgersEmail verificata su rutgers.edu

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Samet Oymak

EECS Prof @ University of Michigan

Email verificata su umich.edu - Home page

machine learning statistics optimization language models


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Gradient descent with early stopping is provably robust to label noise for overparameterized neural networks M Li, M Soltanolkotabi, S Oymak AISTATS, 2020	431	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	390	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	321	2015
Regularized linear regression: A precise analysis of the estimation error C Thrampoulidis, S Oymak, B Hassibi COLT, 2015	271*	2015
Non-asymptotic identification of LTI systems from a single trajectory S Oymak, N Ozay IEEE ACC, 2019	269	2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? S Oymak, M Soltanolkotabi ICML, 2019	221	2019
Unsupervised Multi-source Domain Adaptation Without Access to Source Data SM Ahmed, DS Raychaudhuri, S Paul, S Oymak, AK Roy-Chowdhury CVPR, 2021	194	2021
Transformers as Algorithms: Generalization and Stability in In-context Learning Y Li, ME Ildiz, D Papailiopoulos, S Oymak ICML, 2023	171*	2023
Recovery of sparse 1-D signals from the magnitudes of their Fourier transform K Jaganathan, S Oymak, B Hassibi IEEE ISIT, 2012	163	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	155	2013
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	151	2018
Sparse phase retrieval: Convex algorithms and limitations K Jaganathan, S Oymak, B Hassibi IEEE ISIT, 2013	138	2013
Sparse phase retrieval: Uniqueness guarantees and recovery algorithms K Jaganathan, S Oymak, B Hassibi IEEE Transactions on Signal Processing, 2017	119*	2017
Sharp Time--Data Tradeoffs for Linear Inverse Problems S Oymak, B Recht, M Soltanolkotabi IEEE Transactions on Information Theory, 2018	117	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	109*	2010
Sharp MSE Bounds for Proximal Denoising S Oymak, B Hassibi Foundations of Computational Mathematics, 2013	107	2013
Label-Imbalanced and Group-Sensitive Classification under Overparameterization GR Kini, O Paraskevas, S Oymak, C Thrampoulidis NeurIPS, 2021	101	2021
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	95	2019

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