Individual Q-Learning in Normal Form Games. - David S. Leslie; Edmund J. Collins (SIAM J. Control. Optim., 2005)

Generalised weakened fictitious play. - David S. Leslie; Edmund J. Collins (Games Econ. Behav., 2006)

A general approach to heteroscedastic linear regression. - David S. Leslie; Robert Kohn; David J. Nott (Stat. Comput., 2007)

On Similarities between Inference in Game Theory and Machine Learning. - Iead Rezek; David S. Leslie; Steven Reece; Stephen J. Roberts; Alex Rogers; Rajdeep K. Dash; Nicholas R. Jennings (J. Artif. Intell. Res., 2008)

Sequentially updated Probability Collectives. - Michalis Smyrnakis; David S. Leslie (CDC, 2009)

Convergence of Probability Collectives with Adaptive Choice of Temperature Parameters. - Michalis Smyrnakis; David S. Leslie (LION, 2010)

Dynamic Opponent Modelling in Fictitious Play. - Michalis Smyrnakis; David S. Leslie (Comput. J., 2010)

Posterior Weighted Reinforcement Learning with State Uncertainty. - Tobias Larsen; David S. Leslie; Edmund J. Collins; Rafal Bogacz (Neural Comput., 2010)

Equilibrium selection in potential games with noisy rewards. - David S. Leslie; Jason R. Marden (NetGCoop, 2011)

Adaptive Forgetting Factor Fictitious Play - Michalis Smyrnakis; David S. Leslie (CoRR, 2011)

A unifying framework for iterative approximate best-response algorithms for distributed constraint optimization problems. - Archie C. Chapman; Alex Rogers; Nicholas R. Jennings; David S. Leslie (Knowl. Eng. Rev., 2011)

Optimistic Bayesian Sampling in Contextual-Bandit Problems. - Benedict C. May; Nathan Korda; Anthony Lee; David S. Leslie (J. Mach. Learn. Res., 2012)

Coarse resistance tree methods for stochastic stability analysis. - Holly Borowski; Jason R. Marden; David S. Leslie; Eric W. Frew (CDC, 2013)

Convergent Learning Algorithms for Unknown Reward Games. - Archie C. Chapman; David S. Leslie; Alex Rogers; Nicholas R. Jennings (SIAM J. Control. Optim., 2013)

Learning in Unknown Reward Games: Application to Sensor Networks. - Archie C. Chapman; David S. Leslie; Alex Rogers; Nicholas R. Jennings (Comput. J., 2014)

Game-theoretical control with continuous action sets. - Steven Perkins; Panayotis Mertikopoulos; David S. Leslie (CoRR, 2014)

Stochastic fictitious play with continuous action sets. - Steven Perkins; David S. Leslie (J. Econ. Theory, 2014)

Bayesian Reinforcement Learning in Markovian and non-Markovian Tasks. - Adnane Ez-Zizi; Simon Farrell; David S. Leslie (SSCI, 2015)

Threshold FlipThem: When the winner does not need to take all. - David S. Leslie; Chris Sherfield; Nigel P. Smart (IACR Cryptol. ePrint Arch., 2015)

Why Does Higher Working Memory Capacity Help You Learn? - Kevin Lloyd; Adam Sanborn; David S. Leslie; Stephan Lewandowsky (CogSci, 2017)

Combinatorial Multi-Armed Bandits with Filtered Feedback. - James A. Grant; David S. Leslie; Kevin Glazebrook; Roberto Szechtman (CoRR, 2017)

Multi-Rate Threshold FlipThem. - David S. Leslie; Chris Sherfield; Nigel P. Smart (IACR Cryptol. ePrint Arch., 2017)

Robustness Properties in Fictitious-Play-Type Algorithms. - Brian Swenson; Soummya Kar; João Xavier 001; David S. Leslie (SIAM J. Control. Optim., 2017)

Mixed-Strategy Learning With Continuous Action Sets. - Steven Perkins; Panayotis Mertikopoulos; David S. Leslie (IEEE Trans. Autom. Control., 2017)

Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models. - Henry B. Moss; David S. Leslie; Paul Rayson (COLING, 2018)

Bandit Learning in Concave N-Person Games. - Mario Bravo; David S. Leslie; Panayotis Mertikopoulos (NeurIPS, 2018)

FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms. - Henry B. Moss; Andrew Moore 001; David S. Leslie; Paul Rayson (ACL (1), 2019)

Adaptive Sensor Placement for Continuous Spaces. - James A. Grant; Alexis Boukouvalas; Ryan-Rhys Griffiths; David S. Leslie; Sattar Vakili; Enrique Munoz de Cote (ICML, 2019)

Robust Functional Regression for Outlier Detection. - Harjit Hullait; David S. Leslie; Nicos G. Pavlidis; Steve King 003 (AALTD@PKDD/ECML, 2019)

Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation. - Kevin Lloyd; Adam Sanborn; David S. Leslie; Stephan Lewandowsky (Cogn. Sci., 2019)

On Thompson Sampling for Smoother-than-Lipschitz Bandits. - James A. Grant; David S. Leslie (AISTATS, 2020)

BOSS: Bayesian Optimization over String Spaces. - Henry B. Moss; David S. Leslie; Daniel Beck; Javier Gonzalez; Paul Rayson (NeurIPS, 2020)

MUMBO: MUlti-task Max-Value Bayesian Optimization. - Henry B. Moss; David S. Leslie; Paul Rayson (ECML/PKDD (3), 2020)

BOSH: Bayesian Optimization by Sampling Hierarchically. - Henry B. Moss; David S. Leslie; Paul Rayson (CoRR, 2020)

Adaptive policies for perimeter surveillance problems. - James A. Grant; David S. Leslie; Kevin Glazebrook; Roberto Szechtman; Adam N. Letchford (Eur. J. Oper. Res., 2020)

Best-response dynamics in zero-sum stochastic games. - David S. Leslie; Steven Perkins; Zibo Xu (J. Econ. Theory, 2020)

Selecting multiple web adverts: A contextual multi-armed bandit with state uncertainty. - James A. Edwards; David S. Leslie (J. Oper. Res. Soc., 2020)

Decentralized Q-learning in Zero-sum Markov Games. - Muhammed O. Sayin; Kaiqing Zhang; David S. Leslie; Tamer Basar; Asuman E. Ozdaglar (NeurIPS, 2021)

FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research. - Simen Eide; David S. Leslie; Arnoldo Frigessi; Joakim Rishaug; Helge Jenssen; Sofie Verrewaere (RecSys, 2021)

Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification. - James A. Grant; David S. Leslie (CoRR, 2021)

FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, allViewed Items and Click Responses/No-Click for Recommender Systems Research. - Simen Eide; Arnoldo Frigessi; Helge Jenssen; David S. Leslie; Joakim Rishaug; Sofie Verrewaere (CoRR, 2021)

GIBBON: General-purpose Information-Based Bayesian Optimisation. - Henry B. Moss; David S. Leslie; Javier Gonzalez; Paul Rayson (J. Mach. Learn. Res., 2021)

Robust Function-on-Function Regression. - Harjit Hullait; David S. Leslie; Nicos G. Pavlidis; Steve King 003 (Technometrics, 2021)

Dynamic slate recommendation with gated recurrent units and Thompson sampling. - Simen Eide; David S. Leslie; Arnoldo Frigessi (Data Min. Knowl. Discov., 2022)

Learning to Rank under Multinomial Logit Choice. - James A. Grant; David S. Leslie (J. Mach. Learn. Res., 2023)

A stochastic game framework for patrolling a border. - Matthew Darlington; Kevin D. Glazebrook; David S. Leslie; Rob Shone; Roberto Szechtman (Eur. J. Oper. Res., 2023)

Federated 𝒳-armed Bandit with Flexible Personalisation. - Ali Arabzadeh; James A. Grant; David S. Leslie (Trans. Mach. Learn. Res., 2024)

A Two-Timescale Learning Automata Solution to the Nonlinear Stochastic Proportional Polling Problem. - Anis Yazidi; Hugo Hammer; David S. Leslie (IEEE Trans. Syst. Man Cybern. Syst., 2024)