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researcher

Yufeng Li

16 papers hereh-index 355.1k citations77 works total

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

author position
  • first author2
  • middle author7
  • last author6

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG15
  • cs.CV1
same name
  • Yufeng Li — 28 papers, h 8
  • Yufeng Li — 18 papers, h 20
  • Yufeng Li — 15 papers, h 9
  • Yufeng Li — 14 papers
  • Yufeng Li — 6 papers, h 8
  • Yufeng Li — 5 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

activity
20082022
most citedMulti-Instance Multi-Label Learning

435 citations · 607 across the 16 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022★ 7 cited

A Survey on Extreme Multi-label Learning

Tong Wei, Zhen Mao, Jiang-Xin Shi +2

Multi-label learning has attracted significant attention from both academic and industry field in recent decades. Although existing multi-label learning algorithms achieved good pe…

cs.LG2022★ 42 cited

USB: A Unified Semi-supervised Learning Benchmark for Classification

Yidong Wang, Hao Chen, Yue Fan +19

Semi-supervised learning (SSL) improves model generalization by leveraging massive unlabeled data to augment limited labeled samples. However, currently, popular SSL evaluation pro…

cs.LG2022★ 9 cited

LAMDA-SSL: Semi-Supervised Learning in Python

Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou +1

LAMDA-SSL is open-sourced on GitHub and its detailed usage documentation is available at https://ygzwqzd.github.io/LAMDA-SSL/. This documentation introduces LAMDA-SSL in detail fro…

cs.LG2022★ 4 cited

Robust Deep Semi-Supervised Learning: A Brief Introduction

Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li

Semi-supervised learning (SSL) is the branch of machine learning that aims to improve learning performance by leveraging unlabeled data when labels are insufficient. Recently, SSL…

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