28 citations · 130 across the 23 of their papers we have counts for
26 papers
BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
Rui-Yang Zhang, Lachlan Astfalck, Edward Cripps +2
We introduce a formal active learning methodology for guiding the placement of Lagrangian observers to infer time-dependent vector fields -- a key task in oceanography, marine scie…
A stochastic game framework for patrolling a border
Matthew Darlington, Kevin D. Glazebrook, David S. Leslie +2
In this paper we consider a stochastic game for modelling the interactions between smugglers and a patroller along a border. The problem we examine involves a group of cooperating…
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 +3
We present a novel recommender systems dataset that records the sequential interactions between users and an online marketplace. The users are sequentially presented with both reco…
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification
James A. Grant, David S. Leslie
We consider a variant of online binary classification where a learner sequentially assigns labels ( or ) to items with unknown true class. If, but only if, the learner choose…
Decentralized Q-Learning in Zero-sum Markov Games
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie +2
We study multi-agent reinforcement learning (MARL) in infinite-horizon discounted zero-sum Markov games. We focus on the practical but challenging setting of decentralized MARL, wh…
Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling
Simen Eide, David S. Leslie, Arnoldo Frigessi
We consider the problem of recommending relevant content to users of an internet platform in the form of lists of items, called slates. We introduce a variational Bayesian Recurren…