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20102026
most citedGradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks

154 citations · 861 across the 94 of their papers we have counts for

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cs.IT2015

Sharp Time--Data Tradeoffs for Linear Inverse Problems

Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi

In this paper we characterize sharp time-data tradeoffs for optimization problems used for solving linear inverse problems. We focus on the minimization of a least-squares objectiv…

cs.IT2015

Isometric sketching of any set via the Restricted Isometry Property

Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi

In this paper we show that for the purposes of dimensionality reduction certain class of structured random matrices behave similarly to random Gaussian matrices. This class include…

cs.IT2014★ 20 cited

The Gaussian min-max theorem in the Presence of Convexity

Christos Thrampoulidis, Samet Oymak, Babak Hassibi

Gaussian comparison theorems are useful tools in probability theory; they are essential ingredients in the classical proofs of many results in empirical processes and extreme value…

cs.IT2013★ 16 cited

Simple Bounds for Noisy Linear Inverse Problems with Exact Side Information

Samet Oymak, Christos Thrampoulidis, Babak Hassibi

This paper considers the linear inverse problem where we wish to estimate a structured signal from its corrupted observations. When the problem is ill-posed, it is natural to m…

cs.IT2013

The Squared-Error of Generalized LASSO: A Precise Analysis

Samet Oymak, Christos Thrampoulidis, Babak Hassibi

We consider the problem of estimating an unknown signal from noisy linear observations . In many practical instances, has a certain structure that…

cs.IT2013★ 9 cited

Sparse Phase Retrieval: Uniqueness Guarantees and Recovery Algorithms

Kishore Jaganathan, Samet Oymak, Babak Hassibi

The problem of signal recovery from its Fourier transform magnitude is of paramount importance in various fields of engineering and has been around for over 100 years. Due to the a…