4 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
How much Data do We Need? Sequential Data Collection for Stochastic Programming
Xin Li, Juergen Branke, Xuan Vinh Doan
Data-driven optimization often requires collecting data to estimate uncertain model parameters before solving the underlying decision problem. In practice, however, data acquisitio…
Low-rank matrix recovery with Ky Fan 2-k-norm
Xuan Vinh Doan, Stephen Vavasis
We propose Ky Fan 2-k-norm-based models for the nonconvex low-rank matrix recovery problem. A general difference of convex algorithm (DCA) is developed to solve these models. Numer…
Robust Newsvendor Games with Ambiguity in Demand Distributions
Xuan Vinh Doan, Tri-Dung Nguyen
We investigate newsvendor games whose payoff function is uncertain due to ambiguity in demand distributions. We discuss the concept of stability under uncertainty and introduce sol…
Finding the largest low-rank clusters with Ky Fan --norm and -norm
Xuan Vinh Doan, Stephen Vavasis
We propose a convex optimization formulation with the Ky Fan --norm and -norm to find largest approximately rank-one submatrix blocks of a given nonnegative matri…
A proximal point algorithm for sequential feature extraction applications
Xuan Vinh Doan, Kim-Chuan Toh, Stephen Vavasis
We propose a proximal point algorithm to solve LAROS problem, that is the problem of finding a "large approximately rank-one submatrix". This LAROS problem is used to sequentially…
Finding approximately rank-one submatrices with the nuclear norm and l1 norm
Xuan Vinh Doan, Stephen A. Vavasis
We propose a convex optimization formulation with the nuclear norm and -norm to find a large approximately rank-one submatrix of a given nonnegative matrix. We develop opti…