4 papers · 1 filter
Transfer Learning in Bandits from Unknown Adaptive Policies: Problem-Dependent Lower and Upper Bounds
Adrien Prevost, Timothee Mathieu, Waris Radji +1
Transfer learning in stochastic multi-armed bandits is typically studied assuming that prior data forms a fixed offline dataset or is generated by a known source. In practice, hist…
Information-Based Exploration via Random Features for Reinforcement Learning
Waris Radji, Odalric-Ambrym Maillard
Representation learning has enabled classical exploration strategies to be extended to deep Reinforcement Learning (RL), but often makes algorithms more complex and theoretical gua…
Bandits for Efficient Experimentation: Adapting to Control Group, Preferences, and Context Drifts
Udvas Das, Waris Radji, Debabrota Basu +1
We consider a variant of the linear contextual stochastic multi-armed bandits, where the learner must provide recommendations to a group of users, each having its personalized pref…
Intrinsic-Energy Joint Embedding Predictive Architectures Induce Quasimetric Spaces
Anthony Kobanda, Waris Radji
Joint-Embedding Predictive Architectures (JEPAs) aim to learn representations by predicting target embeddings from context embeddings, inducing a scalar compatibility energy in a l…