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Tao Yang

University of Utah

4 papers hereh-index 8214 citations14 works total

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

author position
  • first author2
  • middle author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.IR4
affiliations
  • University of Utah
Homepage
same name
  • Tao Yang — 22 papers, h 25
  • Tao Yang — 18 papers, h 15
  • Tao Yang — 13 papers, h 9
  • Tao Yang — 12 papers
  • Tao Yang — 9 papers, h 23
  • Tao Yang — 7 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

most citedMaximizing Marginal Fairness for Dynamic Learning to Rank

36 citations · 42 across the 3 of their papers we have counts for

collaborators

4 papers

cs.IR2021

ULTRA: An Unbiased Learning To Rank Algorithm Toolbox

Anh Tran, Tao Yang, Qingyao Ai

Learning to rank systems has become an important aspect of our daily life. However, the implicit user feedback that is used to train many learning to rank models is usually noisy a…

cs.IR2021★ 36 cited

Maximizing Marginal Fairness for Dynamic Learning to Rank

Tao Yang, Qingyao Ai

Rankings, especially those in search and recommendation systems, often determine how people access information and how information is exposed to people. Therefore, how to balance t…

cs.IR2020★ 6 cited

Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank

Tao Yang, Shikai Fang, Shibo Li +2

Leveraging biased click data for optimizing learning to rank systems has been a popular approach in information retrieval. Because click data is often noisy and biased, a variety o…

cs.IR2020

Unbiased Learning to Rank: Online or Offline?

Qingyao Ai, Tao Yang, Huazheng Wang +1

How to obtain an unbiased ranking model by learning to rank with biased user feedback is an important research question for IR. Existing work on unbiased learning to rank (ULTR) ca…

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