24 citations · 69 across the 18 of their papers we have counts for
18 papers
On the Partial Convexification for Low-Rank Spectral Optimization: Rank Bounds and Algorithms
Yongchun Li, Weijun Xie
A Low-rank Spectral Optimization Problem (LSOP) minimizes a linear objective subject to multiple two-sided linear matrix inequalities intersected with a low-rank and spectral const…
ALSO-X#: Better Convex Approximations for Distributionally Robust Chance Constrained Programs
Nan Jiang, Weijun Xie
This paper studies distributionally robust chance constrained programs (DRCCPs), where the uncertain constraints must be satisfied with at least a probability of a prespecified thr…
On the Exactness of Dantzig-Wolfe Relaxation for Rank Constrained Optimization Problems
Yongchun Li, Weijun Xie
In the rank-constrained optimization problem (RCOP), it minimizes a linear objective function over a prespecified closed rank-constrained domain set and generic two-sided linea…
A note on quadratic constraints with indicator variables: Convex hull description and perspective relaxation
Andres Gomez, Weijun Xie
In this paper, we study the mixed-integer nonlinear set given by a separable quadratic constraint on continuous variables, where each continuous variable is controlled by an additi…
D-optimal Data Fusion: Exact and Approximation Algorithms
Yongchun Li, Marcia Fampa, Jon Lee +3
We study the D-optimal Data Fusion (DDF) problem, which aims to select new data points, given an existing Fisher information matrix, so as to maximize the logarithm of the determin…
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…
Second-Order Conic and Polyhedral Approximations of the Exponential Cone: Application to Mixed-Integer Exponential Conic Programs
Qing Ye, Weijun Xie
Exponents and logarithms are fundamental components in many important applications such as logistic regression, maximum likelihood, relative entropy, and so on. Since the exponenti…
Beyond Symmetry: Best Submatrix Selection for the Sparse Truncated SVD
Yongchun Li, Weijun Xie
Truncated singular value decomposition (SVD), also known as the best low-rank matrix approximation, has been successfully applied to many domains such as biology, healthcare, and o…
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…
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…
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…
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…
Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees
Yongchun Li, Weijun Xie
This paper studies a classic maximum entropy sampling problem (MESP), which aims to select the most informative principal submatrix of a prespecified size from a covariance matrix.…
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…
On Distributionally Robust Chance Constrained Programs with Wasserstein Distance
Weijun Xie
This paper studies a distributionally robust chance constrained program (DRCCP) with Wasserstein ambiguity set, where the uncertain constraints should be satisfied with a probabili…
Scalable Algorithms for the Sparse Ridge Regression
Weijun Xie, Xinwei Deng
Sparse regression and variable selection for large-scale data have been rapidly developed in the past decades. This work focuses on sparse ridge regression, which enforces the spar…
Approximation Algorithms for D-optimal Design
Mohit Singh, Weijun Xie
Experimental design is a classical statistics problem and its aim is to estimate an unknown -dimensional vector from linear measurements where a Gaussian noise is introduced…
Optimal Layout of Transshipment Facilities on An Infinite Homogeneous Plane
Weijun Xie, Yanfeng Ouyang
This paper studies optimal spatial layout of transshipment facilities and the corresponding service regions on an infinite homogeneous plane that minimize the total…