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Yong Liu

Alibaba-NTU Singapore Joint Research Institute, Nanyang Technological University

4 papers hereh-index 202.2k citations24 works total

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

author position
  • first author1
  • middle author2
  • last author1

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

fields
  • cs.LG2
  • cs.CL1
  • cs.IR1
affiliations
  • Alibaba-NTU Singapore Joint Research Institute, Nanyang Technological University
Homepage
same name
  • Yong Liu — 27 papers
  • Yong Liu — 23 papers, h 16
  • Yong Liu — 19 papers, h 75
  • Yong Liu — 19 papers
  • Yong Liu — 18 papers
  • Yong Liu — 14 papers

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
20172020
most citedRobust Cost-Sensitive Learning for Recommendation with Implicit Feedback

4 citations · 7 across the 3 of their papers we have counts for

collaborators

4 papers

cs.IR2020★ 2 cited

A Hybrid Bandit Framework for Diversified Recommendation

Qinxu Ding, Yong Liu, Chunyan Miao +2

The interactive recommender systems involve users in the recommendation procedure by receiving timely user feedback to update the recommendation policy. Therefore, they are widely…

cs.CL2020★ 1 cited

Keyword-Guided Neural Conversational Model

Peixiang Zhong, Yong Liu, Hao Wang +1

We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smooth…

cs.LG2018

SL2MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

Yong Liu, Min Wu, Chenghao Liu +2

Synthetic lethality (SL) is a promising concept for novel discovery of anti-cancer drug targets. However, wet-lab experiments for detecting SLs are faced with various challenges, s…

cs.LG2017★ 4 cited

Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback

Peng Yang, Peilin Zhao, Xin Gao +1

Recommendation is the task of improving customer experience through personalized recommendation based on users' past feedback. In this paper, we investigate the most common scenari…

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