Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Tor Lattimore

Minimax Regret for Bandit Convex Optimisation of Ridge Functions

Jun 06, 2021
Tor Lattimore

* Correcting an (instructive) error that leads to a weaker result 

  Access Paper or Ask Questions

Bandit Phase Retrieval

Jun 04, 2021
Tor Lattimore, Botao Hao

  Access Paper or Ask Questions

Information Directed Sampling for Sparse Linear Bandits

May 29, 2021
Botao Hao, Tor Lattimore, Wei Deng

  Access Paper or Ask Questions

On the Optimality of Batch Policy Optimization Algorithms

Apr 06, 2021
Chenjun Xiao, Yifan Wu, Tor Lattimore, Bo Dai, Jincheng Mei, Lihong Li, Csaba Szepesvari, Dale Schuurmans

* 29 pages, 8 figures 

  Access Paper or Ask Questions

Geometric Entropic Exploration

Jan 07, 2021
Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Alaa Saade, Shantanu Thakoor, Bilal Piot, Bernardo Avila Pires, Michal Valko, Thomas Mesnard, Tor Lattimore, Rémi Munos

  Access Paper or Ask Questions

Asymptotically Optimal Information-Directed Sampling

Nov 11, 2020
Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvári

  Access Paper or Ask Questions

High-Dimensional Sparse Linear Bandits

Nov 08, 2020
Botao Hao, Tor Lattimore, Mengdi Wang

* Accepted by NeurIPS 2020 

  Access Paper or Ask Questions

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient

Nov 08, 2020
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang

  Access Paper or Ask Questions

Online Sparse Reinforcement Learning

Nov 08, 2020
Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang

  Access Paper or Ask Questions

Mirror Descent and the Information Ratio

Sep 25, 2020
Tor Lattimore, András György

  Access Paper or Ask Questions

Improved Regret for Zeroth-Order Adversarial Bandit Convex Optimisation

Jun 19, 2020
Tor Lattimore

* 20 pages, 5 figures. Bound is now improved by d^{1/2} 

  Access Paper or Ask Questions

Gaussian Gated Linear Networks

Jun 10, 2020
David Budden, Adam Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness

  Access Paper or Ask Questions

Stochastic matrix games with bandit feedback

Jun 09, 2020
Brendan O'Donoghue, Tor Lattimore, Ian Osband

  Access Paper or Ask Questions

Model Selection in Contextual Stochastic Bandit Problems

Mar 03, 2020
Aldo Pacchiano, My Phan, Yasin Abbasi-Yadkori, Anup Rao, Julian Zimmert, Tor Lattimore, Csaba Szepesvari

* 12 main pages, 2 figures, 14 appendix pages 

  Access Paper or Ask Questions

Information Directed Sampling for Linear Partial Monitoring

Feb 25, 2020
Johannes Kirschner, Tor Lattimore, Andreas Krause

  Access Paper or Ask Questions

Learning with Good Feature Representations in Bandits and in RL with a Generative Model

Nov 18, 2019
Tor Lattimore, Csaba Szepesvari

* 11 pages 

  Access Paper or Ask Questions

Adaptive Exploration in Linear Contextual Bandit

Oct 15, 2019
Botao Hao, Tor Lattimore, Csaba Szepesvari

  Access Paper or Ask Questions

Gated Linear Networks

Sep 30, 2019
Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter

* arXiv admin note: substantial text overlap with arXiv:1712.01897 

  Access Paper or Ask Questions

Behaviour Suite for Reinforcement Learning

Aug 13, 2019
Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepezvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt

  Access Paper or Ask Questions

Iterative Budgeted Exponential Search

Jul 30, 2019
Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant

  Access Paper or Ask Questions

Exploration by Optimisation in Partial Monitoring

Jul 24, 2019
Tor Lattimore, Csaba Szepesvari

* simplified algorithm also works for globally observable, bandit and full information games 

  Access Paper or Ask Questions

Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees

Jun 07, 2019
Laurent Orseau, Levi H. S. Lelis, Tor Lattimore

* This paper and another independent IJCAI 2019 submission have been merged into a single paper that subsumes both of them (Helmert et. al., 2019). This paper is placed here only for historical context. Please only cite the subsuming paper 

  Access Paper or Ask Questions

Connections Between Mirror Descent, Thompson Sampling and the Information Ratio

May 28, 2019
Julian Zimmert, Tor Lattimore

  Access Paper or Ask Questions

Degenerate Feedback Loops in Recommender Systems

Mar 27, 2019
Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli

* Proceedings of AAAI/ACM Conference on AI, Ethics, and Society, Honolulu, HI, USA, January 27-28, 2019 (AIES '19) 

  Access Paper or Ask Questions