4 papers
Minimax Rates for Estimating Powered Sliced Wasserstein Functionals
Binh Thuan Tran
We study the two-sample estimation of the powered Sliced Wasserstein functional under projected -th moment assumptions. Let , where and are two sample sizes…
Sliced Orlicz-Wasserstein
Binh Thuan Tran, Khai Nguyen
We propose sliced Orlicz-Wasserstein (SOW) distance which is a generalization of sliced Wasserstein (SW) distance. SOW replaces the norm in SW with a Luxemburg norm cost indu…
Minimax-Optimal Two-Sample Test with Sliced Wasserstein
Binh Thuan Tran, Nicolas Schreuder
We study the problem of nonparametric two-sample testing using the sliced Wasserstein (SW) distance. While prior theoretical and empirical work indicates that the SW distance offer…
Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
Khoa Nguyen, Viet Huynh, Binh Tran +3
Bayesian Optimization (BO) is a well-established method for addressing black-box optimization problems. In many real-world scenarios, optimization often involves multiple functions…