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Xiangyu Zhao

24 papers hereh-index 313.9k citations60 works total

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

author position
  • first author21
  • middle author3

Across the 24 of 24 papers where every author was matched, so the position is known.

fields
  • cs.IR11
  • cs.CV6
  • cs.LG3
  • cs.CR1
  • cs.CY1
  • eess.IV1
same name
  • Xiangyu Zhao — 43 papers, h 16
  • Xiangyu Zhao — 29 papers, h 10
  • Xiangyu Zhao — 15 papers, h 8
  • Xiangyu Zhao — 14 papers, h 10
  • Xiangyu Zhao — 13 papers, h 9
  • Xiangyu Zhao — 12 papers, h 22

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
20162021
most citedDeep Reinforcement Learning for Page-wise Recommendations

430 citations · 1.4k across the 24 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.IR2019★ 9 cited

DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems

Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang +4

With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in utilizing RL for online advertising in recommendation platforms (e.g., e-commerce…

cs.CV2019

Recognizing Part Attributes with Insufficient Data

Xiangyun Zhao, Yi Yang, Feng Zhou +4

Recognizing attributes of objects and their parts is important to many computer vision applications. Although great progress has been made to apply object-level recognition, recogn…

cs.IR2019★ 17 cited

Toward Simulating Environments in Reinforcement Learning Based Recommendations

Xiangyu Zhao, Long Xia, Lixin Zou +2

With the recent advances in Reinforcement Learning (RL), there have been tremendous interests in employing RL for recommender systems. However, directly training and evaluating a n…

cs.IR2019★ 49 cited

Whole-Chain Recommendations

Xiangyu Zhao, Long Xia, Linxin Zou +3

With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in developing RL-based recommender systems. In practical recommendation sessions, us…

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