255 citations · 2.4k across the 127 of their papers we have counts for
5 papers · 2 filters
Learning with a Strong Adversary
Ruitong Huang, Bing Xu, Dale Schuurmans +1
The robustness of neural networks to intended perturbations has recently attracted significant attention. In this paper, we propose a new method, \emph{learning with a strong adver…
Combinatorial Cascading Bandits
Branislav Kveton, Zheng Wen, Azin Ashkan +1
We propose combinatorial cascading bandits, a class of partial monitoring problems where at each step a learning agent chooses a tuple of ground items subject to constraints and re…
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path
Daniel Hsu, Aryeh Kontorovich, Csaba Szepesvári
This article provides the first procedure for computing a fully data-dependent interval that traps the mixing time of a finite reversible ergodic Markov chain at a…
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control
Prashanth L. A., Cheng Jie, Michael Fu +2
Cumulative prospect theory (CPT) is known to model human decisions well, with substantial empirical evidence supporting this claim. CPT works by distorting probabilities and is mor…
Cascading Bandits: Learning to Rank in the Cascade Model
Branislav Kveton, Csaba Szepesvari, Zheng Wen +1
A search engine usually outputs a list of web pages. The user examines this list, from the first web page to the last, and chooses the first attractive page. This model of user…