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Jianhua Zhao

4 papers hereh-index 323 citations7 works total

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

author position
  • first author2
  • middle author1
  • last author1

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

fields
  • cs.LG2
  • stat.ML2
same name
  • Jianhua Zhao — 25 papers, h 39
  • Jianhua Zhao — 14 papers, h 6
  • Jianhua Zhao — 7 papers, h 3
  • Jianhua Zhao — 3 papers, h 1
  • Jianhua Zhao — 2 papers, h 14
  • Jianhua Zhao — 2 papers, h 1

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

most citedRegularized Bilinear Discriminant Analysis for Multivariate Time Series Data

3 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2024

A Safe Screening Rule with Bi-level Optimization of ν Support Vector Machine

Zhiji Yang, Wanyi Chen, Huan Zhang +3

Support vector machine (SVM) has achieved many successes in machine learning, especially for a small sample problem. As a famous extension of the traditional SVM, the ν support v…

stat.ML2024

Robust bilinear factor analysis based on the matrix-variate t distribution

Xuan Ma, Jianhua Zhao, Changchun Shang +2

Factor Analysis based on multivariate t distribution (tfa) is a useful robust tool for extracting common factors on heavy-tailed or contaminated data. However, tfa is only ap…

stat.ML2022★ 2 cited

Choosing the number of factors in factor analysis with incomplete data via a hierarchical Bayesian information criterion

Jianhua Zhao, Changchun Shang, Shulan Li +2

The Bayesian information criterion (BIC), defined as the observed data log likelihood minus a penalty term based on the sample size N, is a popular model selection criterion for…

cs.LG2022★ 3 cited

Regularized Bilinear Discriminant Analysis for Multivariate Time Series Data

Jianhua Zhao, Haiye Liang, Shulan Li +2

In recent years, the methods on matrix-based or bilinear discriminant analysis (BLDA) have received much attention. Despite their advantages, it has been reported that the traditio…

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