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Xinyue Liu

4 papers hereh-index 7290 citations22 works total

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1
  • cs.IR1
same name
  • Xinyue Liu — 5 papers, h 4
  • Xinyue Liu — 5 papers, h 3
  • Xinyue Liu — 4 papers, h 2
  • Xinyue Liu — 3 papers, h 4
  • Xinyue Liu — 3 papers, h 1
  • Xinyue Liu — 3 papers, h 2

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
20182023
most citedSigned Distance-based Deep Memory Recommender

28 citations · 34 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2023

Multi-State Brain Network Discovery

Hang Yin, Yao Su, Xinyue Liu +3

Brain network discovery aims to find nodes and edges from the spatio-temporal signals obtained by neuroimaging data, such as fMRI scans of human brains. Existing methods tend to de…

cs.LG2021

Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks

Hang Yin, Xinyue Liu, Xiangnan Kong

Sparse inverse covariance estimation (i.e., edge de-tection) is an important research problem in recent years, wherethe goal is to discover the direct connections between a set ofn…

cs.IR2019★ 28 cited

Signed Distance-based Deep Memory Recommender

Thanh Tran, Xinyue Liu, Kyumin Lee +1

Personalized recommendation algorithms learn a user's preference for an item by measuring a distance/similarity between them. However, some of the existing recommendation models (e…

cs.CL2018★ 6 cited

TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks

Xinyue Liu, Xiangnan Kong, Lei Liu +1

Generative Adversarial Networks (GANs) have shown great capacity on image generation, in which a discriminative model guides the training of a generative model to construct images…

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