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Zhiwei Liu

Salesforce AI Research

24 papers hereh-index 15861 citations34 works total

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

author position
  • first author1
  • middle author22

Across the 23 of 24 papers where every author was matched, so the position is known.

fields
  • cs.IR14
  • cs.SI4
  • cs.LG3
  • cs.AI2
  • cs.CV1
affiliations
  • Salesforce AI Research
  • University of Illinois at Chicago
  • University of Electronic Science and Technology of China
Homepage
same name
  • Zhiwei Liu — 41 papers, h 17
  • Zhiwei Liu — 30 papers, h 22
  • Zhiwei Liu — 25 papers, h 9
  • Zhiwei Liu — 8 papers, h 5
  • Zhiwei Liu — 6 papers, h 8
  • Zhiwei Liu — 2 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
20182024
most citedAlleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection

295 citations · 354 across the 24 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2023

Semi-Supervised Clustering via Structural Entropy with Different Constraints

Guangjie Zeng, Hao Peng, Angsheng Li +4

Semi-supervised clustering techniques have emerged as valuable tools for leveraging prior information in the form of constraints to improve the quality of clustering outcomes. Desp…

cs.LG2023★ 1 cited

Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation

Ziwei Fan, Zhiwei Liu, Hao Peng +1

Self-supervised sequential recommendation significantly improves recommendation performance by maximizing mutual information with well-designed data augmentations. However, the mut…

cs.LG2021

Relational Graph Neural Network Design via Progressive Neural Architecture Search

Ailing Zeng, Minhao Liu, Zhiwei Liu +3

We propose a novel solution to addressing a long-standing dilemma in the representation learning of graph neural networks (GNNs): how to effectively capture and represent useful in…

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