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Found 7 papers, 0 papers with code
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification
We consider a variant of online binary classification where a learner sequentially assigns labels ($0$ or $1$) to items with unknown true class.
Learning to Rank under Multinomial Logit Choice
The learning to rank (LTR) framework models this problem as a sequential problem of selecting lists of content and observing where users decide to click.
Filtered Poisson Process Bandit on a Continuum
We consider a version of the continuum armed bandit where an action induces a filtered realisation of a non-homogeneous Poisson process.
On Thompson Sampling for Smoother-than-Lipschitz Bandits
Thompson Sampling is a well established approach to bandit and reinforcement learning problems.
Adaptive Sensor Placement for Continuous Spaces
We consider the problem of adaptively placing sensors along an interval to detect stochastically-generated events.
Adaptive Policies for Perimeter Surveillance Problems
Maximising the detection of intrusions is a fundamental and often critical aim of perimeter surveillance.
Combinatorial Multi-Armed Bandits with Filtered Feedback
Motivated by problems in search and detection we present a solution to a Combinatorial Multi-Armed Bandit (CMAB) problem with both heavy-tailed reward distributions and a new class of feedback, filtered semibandit feedback.
