255 citations · 2.4k across the 127 of their papers we have counts for
3 papers · 2 filters
Online Learning to Rank with Features
Shuai Li, Tor Lattimore, Csaba Szepesvári
We introduce a new model for online ranking in which the click probability factors into an examination and attractiveness function and the attractiveness function is a linear funct…
PAC-Bayes bounds for stable algorithms with instance-dependent priors
Omar Rivasplata, Emilio Parrado-Hernandez, John Shawe-Taylor +2
PAC-Bayes bounds have been proposed to get risk estimates based on a training sample. In this paper the PAC-Bayes approach is combined with stability of the hypothesis learned by a…
TopRank: A practical algorithm for online stochastic ranking
Tor Lattimore, Branislav Kveton, Shuai Li +1
Online learning to rank is a sequential decision-making problem where in each round the learning agent chooses a list of items and receives feedback in the form of clicks from the…