activity
20182022
most citedSmooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee

9 citations · 21 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CV20229 cited

Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee

Bo Shen, Weijun Xie, Zhenyu Kong

The objective of this study is to address the problem of background/foreground separation with missing pixels by combining the video acquisition, video recovery, background/foregro…

stat.ML20205 cited

Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms

Qing Ye, Weijun Xie

As an important problem in modern data analytics, classification has witnessed varieties of applications from different domains. Different from conventional classification approach…

math.OC2020

ALSO-X and ALSO-X+: Better Convex Approximations for Chance Constrained Programs

Nan Jiang, Weijun Xie

In a chance constrained program (CCP), the decision-makers aim to seek the best decision whose probability of violating the uncertainty constraints is within the prespecified risk…

stat.ML20207 cited

Exact and Approximation Algorithms for Sparse PCA

Yongchun Li, Weijun Xie

Sparse PCA (SPCA) is a fundamental model in machine learning and data analytics, which has witnessed a variety of application areas such as finance, manufacturing, biology, healthc…

math.OC2020

Distributionally Robust Bottleneck Combinatorial Problems: Uncertainty Quantification and Robust Decision Making

Weijun Xie, Jie Zhang, Shabbir Ahmed

This paper studies data-driven distributionally robust bottleneck combinatorial problems (DRBCP) with stochastic costs, where the probability distribution of the cost vector is con…

math.OC2019

Tractable Reformulations of Distributionally Robust Two-stage Stochastic Programs with Wasserstein Distance

Weijun Xie

In the optimization under uncertainty, decision-makers first select a wait-and-see policy before any realization of uncertainty and then place a here-and-now decision after the unc…