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researcher

Liyan Xie

16 papers hereh-index 10370 citations17 works total

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

author position
  • sole author1
  • first author8
  • middle author6

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • math.ST9
  • stat.ML4
  • cs.IT1
  • cs.LG1
  • stat.ME1
same name
  • Liyan Xie — 12 papers, h 10
  • Liyan Xie — 8 papers, h 3
  • Liyan Xie — 5 papers, h 2
  • Liyan Xie — 5 papers, h 2
  • Liyan Xie — 2 papers, h 13
  • Liyan Xie — 1 paper

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
20182026
most citedRobust Hypothesis Testing with Wasserstein Uncertainty Sets

6 citations · 14 across the 10 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2023★ 1 cited

Neural Differential Recurrent Neural Network with Adaptive Time Steps

Yixuan Tan, Liyan Xie, Xiuyuan Cheng

The neural Ordinary Differential Equation (ODE) model has shown success in learning complex continuous-time processes from observations on discrete time stamps. In this work, we co…

stat.ML2021

Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data

Shixiang Zhu, Alexander Bukharin, Liyan Xie +4

Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incid…

stat.ML2021

Sequential change-point detection for mutually exciting point processes over networks

Haoyun Wang, Liyan Xie, Yao Xie +2

We present a new CUSUM procedure for sequentially detecting change-point in the self and mutual exciting processes, a.k.a. Hawkes networks using discrete events data. Hawkes networ…

stat.ML2020

Distributionally Robust Weighted k-Nearest Neighbors

Shixiang Zhu, Liyan Xie, Minghe Zhang +2

Learning a robust classifier from a few samples remains a key challenge in machine learning. A major thrust of research has been focused on developing k-nearest neighbor (k-NN)…

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