6 papers
Coordinate-wise Polyhedral Method for Eliciting Multivariate Linear Utility and Univariate Nonlinear Utility Functions
Jiaxin Wei, Jia Liu, Huifu Xu
In this paper, we propose a coordinate-wise polyhedral method (CPM) for cutting polyhedra with theoretical guarantees of convergence. Unlike the existing polyhedral method, which d…
Maximum Utility Split Method for Utility Preference Elicitation
Bo Chen, Jia Liu, Huifu Xu
In this paper, we propose a new approach, called maximum utility split (MUS) scheme, which is built on random utility split (RUS) scheme but with a notable difference: one lottery…
Bayesian Distributionally Robust Nash Equilibrium and Its Application
Jian Liu, Ziheng Su, Huifu Xu
Inspired by the recent work by Shapiro et al. [45], we propose a Bayesian distributionally robust Nash equilibrium (BDRNE) model where each player lacks complete information on the…
Modified Polyhedral Method for Elicitation of Shape-Free Utility and Conservatism Reduction in Robust Optimization
Sainan Zhang, Shaoyan Guo, Melvyn Sim +1
In this paper, we propose a modified polyhedral method to elicit a decision maker's (DM's) nonlinear univariate utility function, which does not rely on explicit information about…
Multistage Robust Average Randomized Spectral Risk Optimization
Qiong Wu, Huifu Xu, Harry Zheng
In this paper, we revisit the multistage spectral risk minimization models proposed by Philpott et al.~\cite{PdF13} and Guigues and Römisch \cite{GuR12} but with some new focuses.…
Statistical Robustness of Kernel Learning Estimator with Respect to Data Perturbation
Sainan Zhang, Huifu Xu, Hailin Sun
Inspired by the recent work [28] on the statistical robustness of empirical risks in reproducing kernel Hilbert space (RKHS) where the training data are potentially perturbed or ev…