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researcher

Chao Zhang

4 papers hereh-index 16795 citations37 works total

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

author position
  • middle author4

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

fields
  • cs.LG2
  • cs.CV1
  • cs.MM1
same name
  • Chao Zhang — 39 papers, h 21
  • Chao Zhang — 38 papers, h 38
  • Chao Zhang — 23 papers, h 22
  • Chao Zhang — 23 papers, h 7
  • Chao Zhang — 23 papers, h 11
  • Chao Zhang — 21 papers, h 14

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
20222024
most citedAdaptive Marginalized Semantic Hashing for Unpaired Cross-Modal Retrieval

52 citations · 88 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024

Fast Disentangled Slim Tensor Learning for Multi-view Clustering

Deng Xu, Chao Zhang, Zechao Li +2

Tensor-based multi-view clustering has recently received significant attention due to its exceptional ability to explore cross-view high-order correlations. However, most existing…

cs.LG2023★ 34 cited

Joint Projection Learning and Tensor Decomposition Based Incomplete Multi-view Clustering

Wei Lv, Chao Zhang, Huaxiong Li +2

Incomplete multi-view clustering (IMVC) has received increasing attention since it is often that some views of samples are incomplete in reality. Most existing methods learn simila…

cs.MM2022★ 52 cited

Adaptive Marginalized Semantic Hashing for Unpaired Cross-Modal Retrieval

Kaiyi Luo, Chao Zhang, Huaxiong Li +2

In recent years, Cross-Modal Hashing (CMH) has aroused much attention due to its fast query speed and efficient storage. Previous literatures have achieved promising results for Cr…

cs.LG2022★ 2 cited

Model-Aware Contrastive Learning: Towards Escaping the Dilemmas

Zizheng Huang, Haoxing Chen, Ziqi Wen +4

Contrastive learning (CL) continuously achieves significant breakthroughs across multiple domains. However, the most common InfoNCE-based methods suffer from some dilemmas, such as…

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