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researcher

Mengde Han

2 papers here

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

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG2

identity via Semantic Scholar / OpenAlex

most citedFairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination

51 citations · 53 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2020★ 51 cited

Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination

Tao Zhang, Tianqing Zhu, Jing Li +3

A growing specter in the rise of machine learning is whether the decisions made by machine learning models are fair. While research is already underway to formalize a machine-learn…

cs.LG2020★ 2 cited

Fairness Constraints in Semi-supervised Learning

Tao Zhang, Tianqing Zhu, Mengde Han +3

Fairness in machine learning has received considerable attention. However, most studies on fair learning focus on either supervised learning or unsupervised learning. Very few cons…

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