Large-scale linear systems, Ax=b, frequently arise in practice and deman...
Sparse tensors appear frequently in distributed deep learning, either as...
In the realm of big data and machine learning, data-parallel, distribute...
Compressed communication, in the form of sparsification or quantization ...
Optimization acceleration techniques such as momentum play a key role in...
The best pair problem aims to find a pair of points that minimize the
di...
Robust principal component analysis (RPCA) is a well-studied problem wit...
We primarily study a special a weighted low-rank approximation of matric...
We propose a surprisingly simple model for supervised video background
e...
Classical principal component analysis (PCA) is not robust to the presen...
Principal component pursuit (PCP) is a state-of-the-art approach for
bac...