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Tor Lattimore

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

49

Venues

11

Active years

2011–2025

Best venue rank

A*

Where they publish

Papers

49 indexed papers, newest first.

YearVenueTitleAuthors
2025COLTThompson Sampling for Bandit Convex Optimisation.Alireza Bakhtiari, Tor Lattimore, Csaba Szepesvri
2024COLTOnline Newton Method for Bandit Convex Optimisation Extended Abstract.Hidde Fokkema, Dirk van der Hoeven, Tor Lattimore, Jack J. Mayo
2023COLTA Second-Order Method for Stochastic Bandit Convex Optimisation.Tor Lattimore, Andrs Gyrgy
2023COLTA Lower Bound for Linear and Kernel Regression with Adaptive Covariates.Tor Lattimore
2023ICMLDistributed Contextual Linear Bandits with Minimax Optimal Communication Cost.Sanae Amani, Tor Lattimore, Andrs Gyrgy, Lin Yang
2023ICMLLeveraging Demonstrations to Improve Online Learning: Quality Matters.Botao Hao, Rahul Jain, Tor Lattimore, Benjamin Van Roy, Zheng Wen
2022COLTMinimax Regret for Partial Monitoring: Infinite Outcomes and Rustichini's Regret.Tor Lattimore
2022COLTReturn of the bias: Almost minimax optimal high probability bounds for adversarial linear bandits.Julian Zimmert, Tor Lattimore
2022ICMLContextual Information-Directed Sampling.Botao Hao, Tor Lattimore, Chao Qin
2021AAAIGated Linear Networks.Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter
2021AISTATSOnline Sparse Reinforcement Learning.Botao Hao, Tor Lattimore, Csaba Szepesvri, Mengdi Wang
2021COLTAsymptotically Optimal Information-Directed Sampling.Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvri
2021COLTImproved Regret for Zeroth-Order Stochastic Convex Bandits.Tor Lattimore, Andrs Gyrgy
2021COLTMirror Descent and the Information Ratio.Tor Lattimore, Andrs Gyrgy
2021ICMLSparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient.Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvri, Mengdi Wang
2021ICMLOn the Optimality of Batch Policy Optimization Algorithms.Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvri, Dale Schuurmans
2021UAIMatrix games with bandit feedback.Brendan O'Donoghue, Tor Lattimore, Ian Osband
2020AISTATSAdaptive Exploration in Linear Contextual Bandit.Botao Hao, Tor Lattimore, Csaba Szepesvri
2020COLTInformation Directed Sampling for Linear Partial Monitoring.Johannes Kirschner, Tor Lattimore, Andreas Krause
2020COLTExploration by Optimisation in Partial Monitoring.Tor Lattimore, Csaba Szepesvri
2020ICLRBehaviour Suite for Reinforcement Learning.Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvri, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt
2020ICMLLearning with Good Feature Representations in Bandits and in RL with a Generative Model.Tor Lattimore, Csaba Szepesvri, Gellrt Weisz
2020ICMLLinear bandits with Stochastic Delayed Feedback.Claire Vernade, Alexandra Carpentier, Tor Lattimore, Giovanni Zappella, Beyza Ermis, Michael Brckner
2019AIESDegenerate Feedback Loops in Recommender Systems.Ray Jiang, Silvia Chiappa, Tor Lattimore, Andrs Gyrgy, Pushmeet Kohli
2019ALTCleaning up the neighborhood: A full classification for adversarial partial monitoring.Tor Lattimore, Csaba Szepesvri
2019COLTAn Information-Theoretic Approach to Minimax Regret in Partial Monitoring.Tor Lattimore, Csaba Szepesvri
2019ICMLGarbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits.Branislav Kveton, Csaba Szepesvri, Sharan Vaswani, Zheng Wen, Tor Lattimore, Mohammad Ghavamzadeh
2019ICMLOnline Learning to Rank with Features.Shuai Li, Tor Lattimore, Csaba Szepesvri
2019IJCAIIterative Budgeted Exponential Search.Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant
2019UAIBubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback.Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvri, Masrour Zoghi
2019UAIOn First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits.Roman Pogodin, Tor Lattimore
2017AISTATSThe End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits.Tor Lattimore, Csaba Szepesvri
2017ALTSoft-Bayes: Prod for Mixtures of Experts with Log-Loss.Laurent Orseau, Tor Lattimore, Shane Legg
2017IJCAIOn Thompson Sampling and Asymptotic Optimality.Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
2016COLTRegret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits.Tor Lattimore
2016ICMLConservative Bandits.Yifan Wu, Roshan Shariff, Tor Lattimore, Csaba Szepesvri
2016UAIThompson Sampling is Asymptotically Optimal in General Environments.Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
2014ALTOn Learning the Optimal Waiting Time.Tor Lattimore, Andrs Gyrgy, Csaba Szepesvri
2014ALTBayesian Reinforcement Learning with Exploration.Tor Lattimore, Marcus Hutter
2014CECFree Lunch for optimisation under the universal distribution.Tom Everitt, Tor Lattimore, Marcus Hutter
2014UAIOptimal Resource Allocation with Semi-Bandit Feedback.Tor Lattimore, Koby Crammer, Csaba Szepesvri
2013ALTConcentration and Confidence for Discrete Bayesian Sequence Predictors.Tor Lattimore, Marcus Hutter, Peter Sunehag
2013ALTUniversal Knowledge-Seeking Agents for Stochastic Environments.Laurent Orseau, Tor Lattimore, Marcus Hutter
2013ICMLThe Sample-Complexity of General Reinforcement Learning.Tor Lattimore, Marcus Hutter, Peter Sunehag
2013TAMCOn Martin-Lf Convergence of Solomonoff's Mixture.Tor Lattimore, Marcus Hutter
2012ALTPAC Bounds for Discounted MDPs.Tor Lattimore, Marcus Hutter
2011ALTAsymptotically Optimal Agents.Tor Lattimore, Marcus Hutter
2011ALTTime Consistent Discounting.Tor Lattimore, Marcus Hutter
2011ALTUniversal Prediction of Selected Bits.Tor Lattimore, Marcus Hutter, Vaibhav Gavane