David S. Leslie

Publication Activity (10 Years)

Years Active: 2005-2023
Publications (10 Years): 36

Top Topics

Bayesian Approaches

Multi Armed Bandit

Recommender Systems

Top Venues

J. Econ. Theory

Eur. J. Oper. Res.

Publications

Matthew Darlington, Kevin D. Glazebrook, David S. Leslie, Rob Shone, Roberto Szechtman
A stochastic game framework for patrolling a border. Eur. J. Oper. Res. 311 (3) (2023)
Simen Eide, David S. Leslie, Arnoldo Frigessi
Dynamic slate recommendation with gated recurrent units and Thompson sampling. Data Min. Knowl. Discov. 36 (5) (2022)
Matthew Darlington, Kevin D. Glazebrook, David S. Leslie, Rob Shone, Roberto Szechtman
A stochastic game framework for patrolling a border. CoRR (2022)
Simen Eide, Arnoldo Frigessi, Helge Jenssen, David S. Leslie, Joakim Rishaug, Sofie Verrewaere
FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, allViewed Items and Click Responses/No-Click for Recommender Systems Research. CoRR (2021)
Simen Eide, David S. Leslie, Arnoldo Frigessi, Joakim Rishaug, Helge Jenssen, Sofie Verrewaere
FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research. RecSys (2021)
Simen Eide, David S. Leslie, Arnoldo Frigessi
Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling. CoRR (2021)
Henry B. Moss, David S. Leslie, Javier Gonzalez, Paul Rayson
GIBBON: General-purpose Information-Based Bayesian OptimisatioN. CoRR (2021)
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
Decentralized Q-Learning in Zero-sum Markov Games. CoRR (2021)
James A. Grant, David S. Leslie
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification. CoRR (2021)
Henry B. Moss, David S. Leslie, Javier Gonzalez, Paul Rayson
GIBBON: General-purpose Information-Based Bayesian Optimisation. J. Mach. Learn. Res. 22 (2021)
Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
Robust Function-on-Function Regression. Technometrics 63 (3) (2021)
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
Decentralized Q-learning in Zero-sum Markov Games. NeurIPS (2021)
James A. Grant, David S. Leslie
On Thompson Sampling for Smoother-than-Lipschitz Bandits. CoRR (2020)
Henry B. Moss, David S. Leslie, Daniel Beck, Javier Gonzalez, Paul Rayson
BOSS: Bayesian Optimization over String Spaces. NeurIPS (2020)
James A. Grant, David S. Leslie
On Thompson Sampling for Smoother-than-Lipschitz Bandits. AISTATS (2020)
David S. Leslie, Steven Perkins, Zibo Xu
Best-response dynamics in zero-sum stochastic games. J. Econ. Theory 189 (2020)
James A. Edwards, David S. Leslie
Selecting multiple web adverts: A contextual multi-armed bandit with state uncertainty. J. Oper. Res. Soc. 71 (1) (2020)
Henry B. Moss, David S. Leslie, Paul Rayson
MUMBO: MUlti-task Max-Value Bayesian Optimization. ECML/PKDD (3) (2020)
Henry B. Moss, Daniel Beck, Javier Gonzalez, David S. Leslie, Paul Rayson
BOSS: Bayesian Optimization over String Spaces. CoRR (2020)
Henry B. Moss, David S. Leslie, Paul Rayson
BOSH: Bayesian Optimization by Sampling Hierarchically. CoRR (2020)
James A. Grant, David S. Leslie, Kevin Glazebrook, Roberto Szechtman, Adam N. Letchford
Adaptive policies for perimeter surveillance problems. Eur. J. Oper. Res. 283 (1) (2020)
James A. Grant, David S. Leslie
Learning to Rank under Multinomial Logit Choice. CoRR (2020)
Henry B. Moss, David S. Leslie, Paul Rayson
MUMBO: MUlti-task Max-value Bayesian Optimization. CoRR (2020)
James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
Adaptive Sensor Placement for Continuous Spaces. ICML (2019)
Henry B. Moss, Andrew Moore, David S. Leslie, Paul Rayson
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms. ACL (1) (2019)
James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
Adaptive Sensor Placement for Continuous Spaces. CoRR (2019)
Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
Robust Functional Regression for Outlier Detection. AALTD@PKDD/ECML (2019)
Henry B. Moss, Andrew Moore, David S. Leslie, Paul Rayson
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms. CoRR (2019)
Mario Bravo, David S. Leslie, Panayotis Mertikopoulos
Bandit Learning in Concave N-Person Games. NeurIPS (2018)
James A. Grant, David S. Leslie, Kevin Glazebrook, Roberto Szechtman, Adam N. Letchford
Adaptive Policies for Perimeter Surveillance Problems. CoRR (2018)
Henry B. Moss, David S. Leslie, Paul Rayson
Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models. COLING (2018)
Henry B. Moss, David S. Leslie, Paul Rayson
Using J-K fold Cross Validation to Reduce Variance When Tuning NLP Models. CoRR (2018)
Mario Bravo, David S. Leslie, Panayotis Mertikopoulos
Bandit learning in concave N-person games. CoRR (2018)
James A. Grant, David S. Leslie, Kevin Glazebrook, Roberto Szechtman
Combinatorial Multi-Armed Bandits with Filtered Feedback. CoRR (2017)
Steven Perkins, Panayotis Mertikopoulos, David S. Leslie
Mixed-Strategy Learning With Continuous Action Sets. IEEE Trans. Autom. Control. 62 (1) (2017)
Brian Swenson, Soummya Kar, João M. F. Xavier, David S. Leslie
Robustness Properties in Fictitious-Play-Type Algorithms. SIAM J. Control. Optim. 55 (5) (2017)
Steven Perkins, David S. Leslie
Stochastic fictitious play with continuous action sets. J. Econ. Theory 152 (2014)
Archie C. Chapman, David S. Leslie, Alex Rogers, Nicholas R. Jennings
Learning in Unknown Reward Games: Application to Sensor Networks. Comput. J. 57 (6) (2014)
Steven Perkins, Panayotis Mertikopoulos, David S. Leslie
Game-theoretical control with continuous action sets. CoRR (2014)
Holly Borowski, Jason R. Marden, David S. Leslie, Eric W. Frew
Coarse resistance tree methods for stochastic stability analysis. CDC (2013)
Archie C. Chapman, David S. Leslie, Alex Rogers, Nicholas R. Jennings
Convergent Learning Algorithms for Unknown Reward Games. SIAM J. Control. Optim. 51 (4) (2013)
Benedict C. May, Nathan Korda, Anthony Lee, David S. Leslie
Optimistic Bayesian Sampling in Contextual-Bandit Problems. J. Mach. Learn. Res. 13 (2012)
Michalis Smyrnakis, David S. Leslie
Adaptive Forgetting Factor Fictitious Play CoRR (2011)
Archie C. Chapman, Alex Rogers, Nicholas R. Jennings, David S. Leslie
A unifying framework for iterative approximate best-response algorithms for distributed constraint optimization problems. Knowl. Eng. Rev. 26 (4) (2011)
David S. Leslie, Jason R. Marden
Equilibrium selection in potential games with noisy rewards. NetGCoop (2011)
Michalis Smyrnakis, David S. Leslie
Convergence of Probability Collectives with Adaptive Choice of Temperature Parameters. LION (2010)
Michalis Smyrnakis, David S. Leslie
Dynamic Opponent Modelling in Fictitious Play. Comput. J. 53 (9) (2010)
Tobias Larsen, David S. Leslie, Edmund J. Collins, Rafal Bogacz
Posterior Weighted Reinforcement Learning with State Uncertainty. Neural Comput. 22 (5) (2010)
Michalis Smyrnakis, David S. Leslie
Sequentially updated Probability Collectives. CDC (2009)
Iead Rezek, David S. Leslie, Steven Reece, Stephen J. Roberts, Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings
On Similarities between Inference in Game Theory and Machine Learning. J. Artif. Intell. Res. 33 (2008)
David S. Leslie, Robert Kohn, David J. Nott
A general approach to heteroscedastic linear regression. Stat. Comput. 17 (2) (2007)
David S. Leslie, Edmund J. Collins
Generalised weakened fictitious play. Games Econ. Behav. 56 (2) (2006)
David S. Leslie, Edmund J. Collins
Individual Q-Learning in Normal Form Games. SIAM J. Control. Optim. 44 (2) (2005)