160 citations · 1.5k across the 122 of their papers we have counts for
4 papers · 2 filters
Online Learning to Rank with Top-k Feedback
Sougata Chaudhuri, Ambuj Tewari
We consider two settings of online learning to rank where feedback is restricted to top ranked items. The problem is cast as an online game between a learner and sequence of users,…
Generalization error bounds for learning to rank: Does the length of document lists matter?
Ambuj Tewari, Sougata Chaudhuri
We consider the generalization ability of algorithms for learning to rank at a query level, a problem also called subset ranking. Existing generalization error bounds necessarily d…
Online Learning to Rank with Feedback at the Top
Sougata Chaudhuri, Ambuj Tewari
We consider an online learning to rank setting in which, at each round, an oblivious adversary generates a list of documents, pertaining to a query, and the learner produces sc…
Mixture Proportion Estimation via Kernel Embedding of Distributions
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
Mixture proportion estimation (MPE) is the problem of estimating the weight of a component distribution in a mixture, given samples from the mixture and component. This problem con…