activity
20172021
most citedClass-conditioned Domain Generalization via Wasserstein Distributional Robust Optimization

4 citations · 5 across the 3 of their papers we have counts for

collaborators

8 papers

cs.LG20214 cited

Class-conditioned Domain Generalization via Wasserstein Distributional Robust Optimization

Jingge Wang, Yang Li, Liyan Xie +1

Given multiple source domains, domain generalization aims at learning a universal model that performs well on any unseen but related target domain. In this work, we focus on the do…

stat.ML2020

Uncertainty Quantification for Inferring Hawkes Networks

Haoyun Wang, Liyan Xie, Alex Cuozzo +2

Multivariate Hawkes processes are commonly used to model streaming networked event data in a wide variety of applications. However, it remains a challenge to extract reliable infer…

math.ST2020

Convex Parameter Recovery for Interacting Marked Processes

Anatoli Juditsky, Arkadi Nemirovski, Liyan Xie +1

We introduce a new general modeling approach for multivariate discrete event data with categorical interacting marks, which we refer to as marked Bernoulli processes. In the propos…

stat.AP20191 cited

Asynchronous Multi-Sensor Change-Point Detection for Seismic Tremors

Liyan Xie, Yao Xie, George V. Moustakides

We consider the sequential change-point detection for asynchronous multi-sensors, where each sensor observe a signal (due to change-point) at different times. We propose an asynchr…

math.ST2018

First-order optimal sequential subspace change-point detection

Liyan Xie, George V. Moustakides, Yao Xie

We consider the sequential change-point detection problem of detecting changes that are characterized by a subspace structure. Such changes are frequent in high-dimensional streami…

stat.ML2018

Robust Hypothesis Testing Using Wasserstein Uncertainty Sets

Rui Gao, Liyan Xie, Yao Xie +1

We develop a novel computationally efficient and general framework for robust hypothesis testing. The new framework features a new way to construct uncertainty sets under the null…