David S. Leslie

Orcid: 0000-0001-5253-7676

According to our database1, David S. Leslie authored at least 46 papers between 2005 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


A stochastic game framework for patrolling a border.
Eur. J. Oper. Res., December, 2023

Dynamic slate recommendation with gated recurrent units and Thompson sampling.
Data Min. Knowl. Discov., 2022

Robust Function-on-Function Regression.
Technometrics, 2021

GIBBON: General-purpose Information-Based Bayesian Optimisation.
J. Mach. Learn. Res., 2021

FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, allViewed Items and Click Responses/No-Click for Recommender Systems Research.
CoRR, 2021

Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification.
CoRR, 2021

FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Decentralized Q-learning in Zero-sum Markov Games.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Selecting multiple web adverts: A contextual multi-armed bandit with state uncertainty.
J. Oper. Res. Soc., 2020

Best-response dynamics in zero-sum stochastic games.
J. Econ. Theory, 2020

Adaptive policies for perimeter surveillance problems.
Eur. J. Oper. Res., 2020

Learning to Rank under Multinomial Logit Choice.
CoRR, 2020

BOSH: Bayesian Optimization by Sampling Hierarchically.
CoRR, 2020

MUMBO: MUlti-task Max-Value Bayesian Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

BOSS: Bayesian Optimization over String Spaces.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On Thompson Sampling for Smoother-than-Lipschitz Bandits.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation.
Cogn. Sci., 2019

Robust Functional Regression for Outlier Detection.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2019

Adaptive Sensor Placement for Continuous Spaces.
Proceedings of the 36th International Conference on Machine Learning, 2019

FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Bandit Learning in Concave N-Person Games.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Mixed-Strategy Learning With Continuous Action Sets.
IEEE Trans. Autom. Control., 2017

Robustness Properties in Fictitious-Play-Type Algorithms.
SIAM J. Control. Optim., 2017

Multi-Rate Threshold FlipThem.
IACR Cryptol. ePrint Arch., 2017

Combinatorial Multi-Armed Bandits with Filtered Feedback.
CoRR, 2017

Why Does Higher Working Memory Capacity Help You Learn?
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Threshold FlipThem: When the winner does not need to take all.
IACR Cryptol. ePrint Arch., 2015

Bayesian Reinforcement Learning in Markovian and non-Markovian Tasks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Stochastic fictitious play with continuous action sets.
J. Econ. Theory, 2014

Game-theoretical control with continuous action sets.
CoRR, 2014

Learning in Unknown Reward Games: Application to Sensor Networks.
Comput. J., 2014

Convergent Learning Algorithms for Unknown Reward Games.
SIAM J. Control. Optim., 2013

Coarse resistance tree methods for stochastic stability analysis.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Optimistic Bayesian Sampling in Contextual-Bandit Problems.
J. Mach. Learn. Res., 2012

A unifying framework for iterative approximate best-response algorithms for distributed constraint optimization problems.
Knowl. Eng. Rev., 2011

Adaptive Forgetting Factor Fictitious Play
CoRR, 2011

Equilibrium selection in potential games with noisy rewards.
Proceedings of the 5th International Conference on NETwork Games, COntrol and OPtimization, 2011

Posterior Weighted Reinforcement Learning with State Uncertainty.
Neural Comput., 2010

Dynamic Opponent Modelling in Fictitious Play.
Comput. J., 2010

Convergence of Probability Collectives with Adaptive Choice of Temperature Parameters.
Proceedings of the Learning and Intelligent Optimization, 4th International Conference, 2010

Sequentially updated Probability Collectives.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

On Similarities between Inference in Game Theory and Machine Learning.
J. Artif. Intell. Res., 2008

A general approach to heteroscedastic linear regression.
Stat. Comput., 2007

Generalised weakened fictitious play.
Games Econ. Behav., 2006

Individual Q-Learning in Normal Form Games.
SIAM J. Control. Optim., 2005