collaborators

5 papers

stat.ML2026

The Partition Principle Revisited: Non-Equal Volume Designs Achieve Minimal Expected Star Discrepancy

Xiaoda Xu

We study the expected star discrepancy under a newly designed class of non-equal volume partitions. The main contributions are twofold. First, we establish a strong partition princ…

math.PR2026

On a Class of Partitions with Lower Expected Star Discrepancy and Its Upper Bound than Jittered Sampling

Xiaoda Xu, Jun Xian

We investigate the expected star discrepancy under a newly designed class of convex equivolume partition models. The main contributions are two-fold. First, we establish a strong p…

math.ST2026

Sharp Non-Asymptotic Bounds for the Star Discrepancy of Double-Infinite Random Matrices via Optimal Covering Numbers

Xiaoda Xu, Jun Xian

We establish sharp non-asymptotic probabilistic bounds for the star discrepancy of double-infinite random matrices -- a canonical model for sequences of random point sets in high d…

math.ST2026

Expected star discrepancy based on stratified sampling

Xiaoda Xu, Jun Xian

We present two main contributions to the expected star discrepancy theory. First, we derive a sharper expected upper bound for jittered sampling, improving the leading constants an…

math.PR2025

Random uniform approximation under weighted importance sampling of a class of stratified input

Jun Xian, Xiaoda Xu

We consider random discrepancy under weighted importance sampling of a class of stratified input. We give the expected discrepancy() upper bound in weighted f…