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08/31/2023
A Note on Randomized Kaczmarz Algorithm for Solving Doubly-Noisy Linear Systems
Large-scale linear systems, Ax=b, frequently arise in practice and deman...
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02/05/2021
DeepReduce: A Sparse-tensor Communication Framework for Distributed Deep Learning
Sparse tensors appear frequently in distributed deep learning, either as...
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04/05/2020
On the Convergence Analysis of Asynchronous SGD for Solving Consistent Linear Systems
In the realm of big data and machine learning, data-parallel, distribute...
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11/19/2019
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning
Compressed communication, in the form of sparsification or quantization ...
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05/28/2019
Direct Nonlinear Acceleration
Optimization acceleration techniques such as momentum play a key role in...
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05/25/2019
Best Pair Formulation & Accelerated Scheme for Non-convex Principal Component Pursuit
The best pair problem aims to find a pair of points that minimize the di...
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05/21/2018
A Nonconvex Projection Method for Robust PCA
Robust principal component analysis (RPCA) is a well-studied problem wit...
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04/15/2018
Weighted Low-Rank Approximation of Matrices and Background Modeling
We primarily study a special a weighted low-rank approximation of matric...
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11/23/2017
Online and Batch Supervised Background Estimation via L1 Regression
We propose a surprisingly simple model for supervised video background e...
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07/04/2017
Weighted Low Rank Approximation for Background Estimation Problems
Classical principal component analysis (PCA) is not robust to the presen...
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07/02/2017
