82 citations · 102 across the 7 of their papers we have counts for
4 papers · 1 filter
A Second-Order Method for Stochastic Bandit Convex Optimisation
Tor Lattimore, András György
We introduce a simple and efficient algorithm for unconstrained zeroth-order stochastic convex bandits and prove its regret is at most $(1 + r/d)[d^{1.5} \sqrt{n} + d^3] polylog(n,…
Leveraging Demonstrations to Improve Online Learning: Quality Matters
Botao Hao, Rahul Jain, Tor Lattimore +2
We investigate the extent to which offline demonstration data can improve online learning. It is natural to expect some improvement, but the question is how, and by how much? We sh…
Bounded Regret for Finite-Armed Structured Bandits
Tor Lattimore, Remi Munos
We study a new type of K-armed bandit problem where the expected return of one arm may depend on the returns of other arms. We present a new algorithm for this general class of pro…
Optimal Resource Allocation with Semi-Bandit Feedback
Tor Lattimore, Koby Crammer, Csaba Szepesvári
We study a sequential resource allocation problem involving a fixed number of recurring jobs. At each time-step the manager should distribute available resources among the jobs in…