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researcher

Xue Li

13 papers hereh-index 446.5k citations201 works total

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

author position
  • middle author7
  • last author6

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL2
  • cs.CV2
  • cs.IR2
  • cs.CR1
  • cs.CY1
same name
  • Xue Li — 15 papers, h 4
  • Xue Li — 11 papers, h 7
  • Xue Li — 6 papers, h 4
  • Xue Li — 6 papers, h 4
  • Xue Li — 6 papers, h 3
  • Xue Li — 5 papers, h 5

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
20152021
most citedDeep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification

199 citations · 236 across the 8 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CL2020★ 4 cited

Learning Causal Bayesian Networks from Text

Farhad Moghimifar, Afshin Rahimi, Mahsa Baktashmotlagh +1

Causal relationships form the basis for reasoning and decision-making in Artificial Intelligence systems. To exploit the large volume of textual data available today, the automatic…

cs.IR2020

A Unified Model for Recommendation with Selective Neighborhood Modeling

Jingwei Ma, Jiahui Wen, Panpan Zhang +2

Neighborhood-based recommenders are a major class of Collaborative Filtering (CF) models. The intuition is to exploit neighbors with similar preferences for bridging unseen user-it…

cs.CR2020★ 4 cited

PrivColl: Practical Privacy-Preserving Collaborative Machine Learning

Yanjun Zhang, Guangdong Bai, Xue Li +3

Collaborative learning enables two or more participants, each with their own training dataset, to collaboratively learn a joint model. It is desirable that the collaboration should…

cs.NE2020★ 1 cited

Learning Various Length Dependence by Dual Recurrent Neural Networks

Chenpeng Zhang, Shuai Li, Mao Ye +2

Recurrent neural networks (RNNs) are widely used as a memory model for sequence-related problems. Many variants of RNN have been proposed to solve the gradient problems of training…

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