204 citations · 730 across the 12 of their papers we have counts for
4 papers · 1 filter
Estimating Position Bias without Intrusive Interventions
Aman Agarwal, Ivan Zaitsev, Xuanhui Wang +3
Presentation bias is one of the key challenges when learning from implicit feedback in search engines, as it confounds the relevance signal. While it was recently shown how counter…
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank
Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang +7
Learning-to-Rank deals with maximizing the utility of a list of examples presented to the user, with items of higher relevance being prioritized. It has several practical applicati…
Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks
Qingyao Ai, Xuanhui Wang, Sebastian Bruch +3
While in a classification or a regression setting a label or a value is assigned to each individual document, in a ranking setting we determine the relevance ordering of the entire…
Offline Comparison of Ranking Functions using Randomized Data
Aman Agarwal, Xuanhui Wang, Cheng Li +2
Ranking functions return ranked lists of items, and users often interact with these items. How to evaluate ranking functions using historical interaction logs, also known as off-po…