David S. Leslie

65 papers A* 4A 2B 2Journal 47Unranked 10
YearRankTypeTitle / Venue / Authors
2025 J jnl
BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields.
CoRR
Rui-Yang Zhang, Henry B. Moss, Lachlan Astfalck, Edward Cripps, David S. Leslie
2024 J jnl
A Two-Timescale Learning Automata Solution to the Nonlinear Stochastic Proportional Polling Problem.
IEEE Trans. Syst. Man Cybern. Syst.
Anis Yazidi, Hugo Hammer, David S. Leslie
2024 J jnl
Federated X-armed Bandit with Flexible Personalisation.
CoRR
Ali Arabzadeh, James A. Grant, David S. Leslie
2024 J jnl
Federated 𝒳-armed Bandit with Flexible Personalisation.
Trans. Mach. Learn. Res.
Ali Arabzadeh, James A. Grant, David S. Leslie
2023 J jnl
A stochastic game framework for patrolling a border.
Eur. J. Oper. Res.
Matthew Darlington, Kevin D. Glazebrook, David S. Leslie, Rob Shone, Roberto Szechtman
2023 J jnl
Learning to Rank under Multinomial Logit Choice.
J. Mach. Learn. Res.
James A. Grant, David S. Leslie
2022 J jnl
A stochastic game framework for patrolling a border.
CoRR
Matthew Darlington, Kevin D. Glazebrook, David S. Leslie, Rob Shone, Roberto Szechtman
2022 J jnl
Dynamic slate recommendation with gated recurrent units and Thompson sampling.
Data Min. Knowl. Discov.
Simen Eide, David S. Leslie, Arnoldo Frigessi
2021 J jnl
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification.
CoRR
James A. Grant, David S. Leslie
2021 J jnl
Decentralized Q-Learning in Zero-sum Markov Games.
CoRR
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
2021 A* conf
Decentralized Q-learning in Zero-sum Markov Games.
NeurIPS
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
2021 J jnl
Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling.
CoRR
Simen Eide, David S. Leslie, Arnoldo Frigessi
2021 A conf
FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research.
RecSys
Simen Eide, David S. Leslie, Arnoldo Frigessi, Joakim Rishaug, Helge Jenssen, Sofie Verrewaere
2021 J jnl
FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, allViewed Items and Click Responses/No-Click for Recommender Systems Research.
CoRR
Simen Eide, Arnoldo Frigessi, Helge Jenssen, David S. Leslie, Joakim Rishaug, Sofie Verrewaere
2021 J jnl
GIBBON: General-purpose Information-Based Bayesian OptimisatioN.
CoRR
Henry B. Moss, David S. Leslie, Javier González, Paul Rayson
2021 J jnl
GIBBON: General-purpose Information-Based Bayesian Optimisation.
J. Mach. Learn. Res.
Henry B. Moss, David S. Leslie, Javier González, Paul Rayson
2021 J jnl
Robust Function-on-Function Regression.
Technometrics
Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
2020 J jnl
Adaptive policies for perimeter surveillance problems.
Eur. J. Oper. Res.
James A. Grant, David S. Leslie, Kevin Glazebrook, Roberto Szechtman, Adam N. Letchford
2020 J jnl
BOSH: Bayesian Optimization by Sampling Hierarchically.
CoRR
Henry B. Moss, David S. Leslie, Paul Rayson
2020 A* conf
BOSS: Bayesian Optimization over String Spaces.
NeurIPS
Henry B. Moss, David S. Leslie, Daniel Beck, Javier González, Paul Rayson
2020 J jnl
BOSS: Bayesian Optimization over String Spaces.
CoRR
Henry B. Moss, Daniel Beck, Javier González, David S. Leslie, Paul Rayson
2020 J jnl
Best-response dynamics in zero-sum stochastic games.
J. Econ. Theory
David S. Leslie, Steven Perkins, Zibo Xu
2020 J jnl
Learning to Rank under Multinomial Logit Choice.
CoRR
James A. Grant, David S. Leslie
2020 — conf
MUMBO: MUlti-task Max-Value Bayesian Optimization.
ECML/PKDD (3)
Henry B. Moss, David S. Leslie, Paul Rayson
2020 J jnl
MUMBO: MUlti-task Max-value Bayesian Optimization.
CoRR
Henry B. Moss, David S. Leslie, Paul Rayson
2020 A conf
On Thompson Sampling for Smoother-than-Lipschitz Bandits.
AISTATS
James A. Grant, David S. Leslie
2020 J jnl
On Thompson Sampling for Smoother-than-Lipschitz Bandits.
CoRR
James A. Grant, David S. Leslie
2020 J jnl
Selecting multiple web adverts: A contextual multi-armed bandit with state uncertainty.
J. Oper. Res. Soc.
James A. Edwards, David S. Leslie
2019 A* conf
Adaptive Sensor Placement for Continuous Spaces.
ICML
James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
2019 J jnl
Adaptive Sensor Placement for Continuous Spaces.
CoRR
James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
2019 — conf
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms.
ACL (1)
Henry B. Moss, Andrew Moore, David S. Leslie, Paul Rayson
2019 J jnl
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms.
CoRR
Henry B. Moss, Andrew Moore, David S. Leslie, Paul Rayson
2019 — conf
Robust Functional Regression for Outlier Detection.
AALTD@PKDD/ECML
Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
2019 J jnl
Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation.
Cogn. Sci.
Kevin Lloyd, Adam Sanborn, David S. Leslie, Stephan Lewandowsky
2018 J jnl
Adaptive Policies for Perimeter Surveillance Problems.
CoRR
James A. Grant, David S. Leslie, Kevin Glazebrook, Roberto Szechtman, Adam N. Letchford
2018 A* conf
Bandit Learning in Concave N-Person Games.
NeurIPS
Mario Bravo, David S. Leslie, Panayotis Mertikopoulos
2018 J jnl
Bandit learning in concave N-person games.
CoRR
Mario Bravo, David S. Leslie, Panayotis Mertikopoulos
2018 J jnl
Using J-K fold Cross Validation to Reduce Variance When Tuning NLP Models.
CoRR
Henry B. Moss, David S. Leslie, Paul Rayson
2018 B conf
Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models.
COLING
Henry B. Moss, David S. Leslie, Paul Rayson
2017 J jnl
Combinatorial Multi-Armed Bandits with Filtered Feedback.
CoRR
James A. Grant, David S. Leslie, Kevin Glazebrook, Roberto Szechtman
2017 J jnl
Mixed-Strategy Learning With Continuous Action Sets.
IEEE Trans. Autom. Control.
Steven Perkins, Panayotis Mertikopoulos, David S. Leslie
2017 J jnl
Multi-Rate Threshold FlipThem.
IACR Cryptol. ePrint Arch.
David S. Leslie, Chris Sherfield, Nigel P. Smart
2017 — conf
Multi-rate Threshold FlipThem.
ESORICS (2)
David S. Leslie, Chris Sherfield, Nigel P. Smart
2017 J jnl
Robustness Properties in Fictitious-Play-Type Algorithms.
SIAM J. Control. Optim.
Brian Swenson, Soummya Kar, João Xavier, David S. Leslie
2017 B conf
Why Does Higher Working Memory Capacity Help You Learn?
CogSci
Kevin Lloyd, Adam Sanborn, David S. Leslie, Stephan Lewandowsky
2015 — conf
Bayesian Reinforcement Learning in Markovian and non-Markovian Tasks.
SSCI
Adnane Ez-Zizi, Simon Farrell, David S. Leslie
2015 — conf
Threshold FlipThem: When the Winner Does Not Need to Take All.
GameSec
David S. Leslie, Chris Sherfield, Nigel P. Smart
2015 J jnl
Threshold FlipThem: When the winner does not need to take all.
IACR Cryptol. ePrint Arch.
David S. Leslie, Chris Sherfield, Nigel P. Smart
2014 J jnl
Game-theoretical control with continuous action sets.
CoRR
Steven Perkins, Panayotis Mertikopoulos, David S. Leslie
2014 J jnl
Learning in Unknown Reward Games: Application to Sensor Networks.
Comput. J.
Archie C. Chapman, David S. Leslie, Alex Rogers, Nicholas R. Jennings
2014 J jnl
Stochastic fictitious play with continuous action sets.
J. Econ. Theory
Steven Perkins, David S. Leslie
2013 — conf
Coarse resistance tree methods for stochastic stability analysis.
CDC
Holly Borowski, Jason R. Marden, David S. Leslie, Eric W. Frew
2013 J jnl
Convergent Learning Algorithms for Unknown Reward Games.
SIAM J. Control. Optim.
Archie C. Chapman, David S. Leslie, Alex Rogers, Nicholas R. Jennings
2012 J jnl
Optimistic Bayesian Sampling in Contextual-Bandit Problems.
J. Mach. Learn. Res.
Benedict C. May, Nathan Korda, Anthony Lee, David S. Leslie
2011 J jnl
A unifying framework for iterative approximate best-response algorithms for distributed constraint optimization problems.
Knowl. Eng. Rev.
Archie C. Chapman, Alex Rogers, Nicholas R. Jennings, David S. Leslie
2011 J jnl
Adaptive Forgetting Factor Fictitious Play
CoRR
Michalis Smyrnakis, David S. Leslie
2011 — conf
Equilibrium selection in potential games with noisy rewards.
NetGCoop
David S. Leslie, Jason R. Marden
2010 — conf
Convergence of Probability Collectives with Adaptive Choice of Temperature Parameters.
LION
Michalis Smyrnakis, David S. Leslie
2010 J jnl
Dynamic Opponent Modelling in Fictitious Play.
Comput. J.
Michalis Smyrnakis, David S. Leslie
2010 J jnl
Posterior Weighted Reinforcement Learning with State Uncertainty.
Neural Comput.
Tobias Larsen, David S. Leslie, Edmund J. Collins, Rafal Bogacz
2009 — conf
Sequentially updated Probability Collectives.
CDC
Michalis Smyrnakis, David S. Leslie
2008 J jnl
On Similarities between Inference in Game Theory and Machine Learning.
J. Artif. Intell. Res.
Iead Rezek, David S. Leslie, Steven Reece, Stephen J. Roberts, Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings
2007 J jnl
A general approach to heteroscedastic linear regression.
Stat. Comput.
David S. Leslie, Robert Kohn, David J. Nott
2006 J jnl
Generalised weakened fictitious play.
Games Econ. Behav.
David S. Leslie, Edmund J. Collins
2005 J jnl
Individual Q-Learning in Normal Form Games.
SIAM J. Control. Optim.
David S. Leslie, Edmund J. Collins