153 citations · 381 across the 39 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…
Linear Bandits with Stochastic Delayed Feedback
Claire Vernade, Alexandra Carpentier, Tor Lattimore +3
Stochastic linear bandits are a natural and well-studied model for structured exploration/exploitation problems and are widely used in applications such as online marketing and rec…
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…