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01/22/2022
The Forward-Backward Envelope for Sampling with the Overdamped Langevin Algorithm
In this paper, we analyse a proximal method based on the idea of forward...
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12/25/2021
Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points
Motivated by the emerging role of interpolating machines in signal proce...
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11/02/2021
Subquadratic Overparameterization for Shallow Neural Networks
Overparameterization refers to the important phenomenon where the width ...
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09/13/2021
Nonlinear matrix recovery using optimization on the Grassmann manifold
We investigate the problem of recovering a partially observed high-rank ...
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05/25/2021
Principal Component Hierarchy for Sparse Quadratic Programs
We propose a novel approximation hierarchy for cardinality-constrained, ...
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01/07/2021
The Nonconvex Geometry of Linear Inverse Problems
The gauge function, closely related to the atomic norm, measures the com...
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08/27/2020
Implicit Regularization in Matrix Sensing: A Geometric View Leads to Stronger Results
We may think of low-rank matrix sensing as a learning problem with infin...
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07/02/2020
Double-Loop Unadjusted Langevin Algorithm
A well-known first-order method for sampling from log-concave probabilit...
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10/09/2019
Nearly Minimal Over-Parametrization of Shallow Neural Networks
A recent line of work has shown that an overparametrized neural network ...
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07/07/2019
Fast and Provable ADMM for Learning with Generative Priors
In this work, we propose a (linearized) Alternating Direction Method-of-...
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06/04/2018
MOSES: A Streaming Algorithm for Linear Dimensionality Reduction
This paper introduces Memory-limited Online Subspace Estimation Scheme (...
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05/24/2018
Stable Super-Resolution of Images
We study the ubiquitous problem of super-resolution in which one aims at...
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04/04/2018