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researcher

Yitong Li

The University of Melbourne

17 papers hereh-index 171.5k citations45 works total

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

author position
  • first author7
  • middle author7
  • last author1

Across the 15 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CL5
  • eess.SY5
  • cs.LG3
  • cs.CR2
  • cs.CV1
  • cs.SE1
affiliations
  • The University of Melbourne
  • Huawei Technologies Co., Ltd.
Homepage
same name
  • Yitong Li — 16 papers, h 7
  • Yitong Li — 12 papers, h 11
  • Yitong Li — 9 papers, h 8
  • Yitong Li — 8 papers, h 7
  • Yitong Li — 8 papers, h 2
  • Yitong Li — 7 papers, h 10

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
20162026
most citedHow to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning

31 citations · 46 across the 10 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2022★ 8 cited

fairlib: A Unified Framework for Assessing and Improving Classification Fairness

Xudong Han, Aili Shen, Yitong Li +3

This paper presents fairlib, an open-source framework for assessing and improving classification fairness. It provides a systematic framework for quickly reproducing existing basel…

cs.LG2020★ 6 cited

Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness

Lingjuan Lyu, Xuanli He, Yitong Li

It has been demonstrated that hidden representation learned by a deep model can encode private information of the input, hence can be exploited to recover such information with rea…

cs.LG2020★ 1 cited

Towards Differentially Private Text Representations

Lingjuan Lyu, Yitong Li, Xuanli He +1

Most deep learning frameworks require users to pool their local data or model updates to a trusted server to train or maintain a global model. The assumption of a trusted server wh…

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