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papers

Publications (28)

cs.DS2016

Near-Optimal Sample Complexity Bounds for Circulant Binary Embedding

Samet Oymak

cs.LG2019

Towards moderate overparameterization: global convergence guarantees for training shallow neural networks

Samet Oymak, Mahdi Soltanolkotabi

cs.LG2019

Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks

Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak

cs.DC2015

Parallel Correlation Clustering on Big Graphs

Xinghao Pan, Dimitris Papailiopoulos, Samet Oymak +3

cs.IT2012

Recovery of Sparse 1-D Signals from the Magnitudes of their Fourier Transform

Kishore Jaganathan, Samet Oymak, Babak Hassibi

stat.ML2011

Finding Dense Clusters via "Low Rank + Sparse" Decomposition

Samet Oymak, Babak Hassibi

cs.IT2015

Sparse Phase Retrieval: Uniqueness Guarantees and Recovery Algorithms

Kishore Jaganathan, Samet Oymak, Babak Hassibi

cs.IT2014

Simultaneously Structured Models with Application to Sparse and Low-rank Matrices

Samet Oymak, Amin Jalali, Maryam Fazel +2

math.OC2010

New Null Space Results and Recovery Thresholds for Matrix Rank Minimization

Samet Oymak, Babak Hassibi

cs.LG2019

Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian

Samet Oymak, Zalan Fabian, Mingchen Li +1

cs.LG2018

Stochastic Gradient Descent Learns State Equations with Nonlinear Activations

Samet Oymak

cs.LG2018

Learning Compact Neural Networks with Regularization

Samet Oymak

cs.IT2013

Simple Bounds for Noisy Linear Inverse Problems with Exact Side Information

Samet Oymak, Christos Thrampoulidis, Babak Hassibi

cs.LG2018

Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?

Samet Oymak, Mahdi Soltanolkotabi

cs.IT2013

Sparse Phase Retrieval: Convex Algorithms and Limitations

Kishore Jaganathan, Samet Oymak, Babak Hassibi

cs.IT2011

Subspace Expanders and Matrix Rank Minimization

Amin Khajehnejad, Samet Oymak, Babak Hassibi

math.PR2017

Universality laws for randomized dimension reduction, with applications

Samet Oymak, Joel A. Tropp

cs.IT2013

Sharp MSE Bounds for Proximal Denoising

Samet Oymak, Babak Hassibi

stat.ML2016

Fast and Reliable Parameter Estimation from Nonlinear Observations

Samet Oymak, Mahdi Soltanolkotabi

cs.LG2015

Near-Optimal Bounds for Binary Embeddings of Arbitrary Sets

Samet Oymak, Ben Recht

cs.IT2012

Recovering Jointly Sparse Signals via Joint Basis Pursuit

Samet Oymak, Babak Hassibi

cs.IT2016

Sharp Time--Data Tradeoffs for Linear Inverse Problems

Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi

cs.IT2015

Isometric sketching of any set via the Restricted Isometry Property

Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi

math.OC2014

Simple Error Bounds for Regularized Noisy Linear Inverse Problems

Christos Thrampoulidis, Samet Oymak, Babak Hassibi

cs.LG2018

End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition

Samet Oymak, Mahdi Soltanolkotabi

cs.IT2013

The Squared-Error of Generalized LASSO: A Precise Analysis

Samet Oymak, Christos Thrampoulidis, Babak Hassibi

cs.IT2015

The Gaussian min-max theorem in the Presence of Convexity

Christos Thrampoulidis, Samet Oymak, Babak Hassibi

cs.LG2017

Learning Feature Nonlinearities with Non-Convex Regularized Binned Regression

Samet Oymak, Mehrdad Mahdavi, Jiasi Chen