791 citations · 2.5k across the 66 of their papers we have counts for
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math.NA2017★ 5 cited
Scalable Robust Matrix Factorization with Nonconvex Loss
Quanming Yao, James T. Kwok
Robust matrix factorization (RMF), which uses the -loss, often outperforms standard matrix factorization using the -loss, particularly when outliers are present. Th…
math.NA2017★ 4 cited
Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion
Quanming Yao, James T. Kwok
Matrix and tensor completion aim to recover a low-rank matrix / tensor from limited observations and have been commonly used in applications such as recommender systems and multi-r…
math.NA2015★ 16 cited
Fast Low-Rank Matrix Learning with Nonconvex Regularization
Quanming Yao, James T. Kwok, Wenliang Zhong
Low-rank modeling has a lot of important applications in machine learning, computer vision and social network analysis. While the matrix rank is often approximated by the convex nu…