255 citations · 2.4k across the 127 of their papers we have counts for
3 papers · 2 filters
Asymptotically Optimal Information-Directed Sampling
Johannes Kirschner, Tor Lattimore, Claire Vernade +1
We introduce a simple and efficient algorithm for stochastic linear bandits with finitely many actions that is asymptotically optimal and (nearly) worst-case optimal in finite time…
A Distribution-Dependent Analysis of Meta-Learning
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári
A key problem in the theory of meta-learning is to understand how the task distributions influence transfer risk, the expected error of a meta-learner on a new task drawn from the…
PAC-Bayes Analysis Beyond the Usual Bounds
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvari +1
We focus on a stochastic learning model where the learner observes a finite set of training examples and the output of the learning process is a data-dependent distribution over a…