4 papers · 1 filter
Theoretical Foundations of @ Reinforcement Learning
Riccardo Poiani, Martino Bernasconi, Andrea Celli
Reinforcement Learning is a cornerstone technique for modern large reasoning models. Usually, for difficult tasks such as code generation and theorem proving, the agent is evaluate…
Online Learning in the Random Order Model
Martino Bernasconi, Andrea Celli, Riccardo Colini-Baldeschi +3
In the random-order model for online learning, the sequence of losses is chosen upfront by an adversary and presented to the learner after a random permutation. Any random-order in…
Non-Asymptotic Analysis of (Sticky) Track-and-Stop
Riccardo Poiani, Martino Bernasconi, Andrea Celli
In pure exploration problems, a statistician sequentially collects information to answer a question about some stochastic and unknown environment. The probability of returning a wr…
Pure Exploration with Infinite Answers
Riccardo Poiani, Martino Bernasconi, Andrea Celli
We study pure exploration problems in which the set of correct answers is possibly infinite. For example, such problems arise when regressing a continuous function on the means of…