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Zhi Chen

13 papers hereh-index 102k citations17 works total

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

author position
  • first author3
  • middle author10

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

fields
  • cs.LG8
  • cs.CL1
  • cs.CV1
  • cs.HC1
  • physics.app-ph1
  • stat.ML1
same name
  • Zhi Chen — 39 papers, h 41
  • Zhi Chen — 29 papers, h 11
  • Zhi Chen — 14 papers, h 25
  • Zhi Chen — 14 papers, h 14
  • Zhi Chen — 13 papers, h 6
  • Zhi Chen — 13 papers, h 8

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
20172024
most citedConcept Whitening for Interpretable Image Recognition

283 citations · 490 across the 13 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CL2023

CLEVA: Chinese Language Models EVAluation Platform

Yanyang Li, Jianqiao Zhao, Duo Zheng +8

With the continuous emergence of Chinese Large Language Models (LLMs), how to evaluate a model's capabilities has become an increasingly significant issue. The absence of a compreh…

cs.LG2023★ 2 cited

Provable Multi-instance Deep AUC Maximization with Stochastic Pooling

Dixian Zhu, Bokun Wang, Zhi Chen +4

This paper considers a novel application of deep AUC maximization (DAM) for multi-instance learning (MIL), in which a single class label is assigned to a bag of instances (e.g., mu…

cs.LG2023★ 5 cited

Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?

Zhi Chen, Sarah Tan, Urszula Chajewska +2

Missing values are a fundamental problem in data science. Many datasets have missing values that must be properly handled because the way missing values are treated can have large…

cs.LG2023★ 1 cited

Exploring and Interacting with the Set of Good Sparse Generalized Additive Models

Chudi Zhong, Zhi Chen, Jiachang Liu +2

In real applications, interaction between machine learning models and domain experts is critical; however, the classical machine learning paradigm that usually produces only a sing…

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