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Xiangli Yang

6 papers hereh-index 101.4k citations18 works total

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

author position
  • first author3
  • middle author2

Across the 5 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL1
  • cs.IR1
same name
  • Xiangli Yang — 1 paper, h 7
  • Xiangli Yang — 1 paper, h 3
  • Xiangli Yang — 1 paper, h 2

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
20212023
most citedA Survey on Deep Semi-supervised Learning

903 citations · 947 across the 6 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.LG2021

DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training

Xianglin Yang, Yun Lin, Ruofan Liu +4

Understanding how the predictions of deep learning models are formed during the training process is crucial to improve model performance and fix model defects, especially when we n…

cs.IR2021★ 4 cited

AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction

Xiangli Yang, Qing Liu, Rong Su +3

Recommender systems are often asked to serve multiple recommendation scenarios or domains. Fine-tuning a pre-trained CTR model from source domains and adapting it to a target domai…

cs.LG2021★ 903 cited

A Survey on Deep Semi-supervised Learning

Xiangli Yang, Zixing Song, Irwin King +1

Deep semi-supervised learning is a fast-growing field with a range of practical applications. This paper provides a comprehensive survey on both fundamentals and recent advances in…

cs.LG2021★ 26 cited

Graph-based Semi-supervised Learning: A Comprehensive Review

Zixing Song, Xiangli Yang, Zenglin Xu +1

Semi-supervised learning (SSL) has tremendous value in practice due to its ability to utilize both labeled data and unlabelled data. An important class of SSL methods is to natural…

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