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Liyan Xie

8 papers hereh-index 102.5k citations24 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author5

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • math.ST4
  • stat.ML2
  • cs.LG1
  • stat.AP1
same name
  • Liyan Xie — 7 papers, h 10
  • Liyan Xie — 5 papers, h 2
  • Liyan Xie — 3 papers, h 3
  • Liyan Xie — 3 papers, h 2
  • Liyan Xie — 2 papers
  • Liyan Xie — 2 papers, h 13

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

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
Showing math.STShow all

4 papers · 1 filter

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…

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…

math.ST2017

Sequential detection of low-rank changes using extreme eigenvalues

Liyan Xie, Yao Xie

We study the problem of detecting an abrupt change to the signal covariance matrix. In particular, the covariance changes from a "white" identity matrix to an unknown spiked or low…

math.ST2017

Nearly second-order asymptotic optimality of sequential change-point detection with one-sample updates

Yang Cao, Liyan Xie, Yao Xie +1

Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unkn…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.