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02/15/2023
Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
This paper studies the role of over-parametrization in solving non-conve...
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08/15/2022
Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing
Many fundamental low-rank optimization problems, such as matrix completi...
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03/08/2022
Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate
This paper is concerned with low-rank matrix optimization, which has fou...
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05/18/2021
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements
In this paper, we study a general low-rank matrix recovery problem with ...
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01/22/2021
Partition-Based Convex Relaxations for Certifying the Robustness of ReLU Neural Networks
In this paper, we study certifying the robustness of ReLU neural network...
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10/16/2020
Strengthened SDP Verification of Neural Network Robustness via Non-Convex Cuts
There have been major advances on the design of neural networks, but sti...
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04/01/2020
Tightened Convex Relaxations for Neural Network Robustness Certification
In this paper, we consider the problem of certifying the robustness of n...
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09/10/2018
