112 citations · 173 across the 4 of their papers we have counts for
4 papers
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…
Budget-Constrained Item Cold-Start Handling in Collaborative Filtering Recommenders via Optimal Design
Oren Anava, Shahar Golan, Nadav Golbandi +4
It is well known that collaborative filtering (CF) based recommender systems provide better modeling of users and items associated with considerable rating history. The lack of his…
Hierarchical Composable Optimization of Web Pages
Ronen Barenboim, Edward Bortnikov, Nadav Golbandi +6
The process of creating modern Web media experiences is challenged by the need to adapt the content and presentation choices to dynamic real-time fluctuations of user interest acro…