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20182026
most citedRapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation

64 citations · 179 across the 24 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024

Guaranteed Sampling Flexibility for Low-tubal-rank Tensor Completion

Bowen Su, Juntao You, HanQin Cai +1

While Bernoulli sampling is extensively studied in tensor completion, t-CUR sampling approximates low-tubal-rank tensors via lateral and horizontal subtensors. However, both method…

cs.LG2023★ 1 cited

Non-convex approaches for low-rank tensor completion under tubal sampling

Zheng Tan, Longxiu Huang, HanQin Cai +1

Tensor completion is an important problem in modern data analysis. In this work, we investigate a specific sampling strategy, referred to as tubal sampling. We propose two novel no…

cs.LG2022★ 18 cited

Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling

HanQin Cai, Longxiu Huang, Pengyu Li +1

While uniform sampling has been widely studied in the matrix completion literature, CUR sampling approximates a low-rank matrix via row and column samples. Unfortunately, both samp…

cs.LG2022

Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents

Pengyu Li, Christine Tseng, Yaxuan Zheng +4

Classification and topic modeling are popular techniques in machine learning that extract information from large-scale datasets. By incorporating a priori information such as label…

cs.LG2021★ 2 cited

Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition

HanQin Cai, Zehan Chao, Longxiu Huang +1

We study the problem of tensor robust principal component analysis (TRPCA), which aims to separate an underlying low-multilinear-rank tensor and a sparse outlier tensor from their…