79 citations · 519 across the 58 of their papers we have counts for
66 papers
On Universally Optimal Algorithms for A/B Testing
Po-An Wang, Kaito Ariu, Alexandre Proutiere
We study the problem of best-arm identification with fixed budget in stochastic multi-armed bandits with Bernoulli rewards. For the problem with two arms, also known as the A/B tes…
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
Kaito Ariu, Alexandre Proutiere, Se-Young Yun
In this paper, we investigate the problem of recovering hidden communities in the Labeled Stochastic Block Model (LSBM) with a finite number of clusters whose sizes grow linearly w…
Conformal Off-Policy Evaluation in Markov Decision Processes
Daniele Foffano, Alessio Russo, Alexandre Proutiere
Reinforcement Learning aims at identifying and evaluating efficient control policies from data. In many real-world applications, the learner is not allowed to experiment and cannot…
On the Sample Complexity of Representation Learning in Multi-task Bandits with Global and Local structure
Alessio Russo, Alexandre Proutiere
We investigate the sample complexity of learning the optimal arm for multi-task bandit problems. Arms consist of two components: one that is shared across tasks (that we call repre…
Self-Tuning Tube-based Model Predictive Control
Damianos Tranos, Alessio Russo, Alexandre Proutiere
We present Self-Tuning Tube-based Model Predictive Control (STT-MPC), an adaptive robust control algorithm for uncertain linear systems with additive disturbances based on the leas…
Tube-Based Zonotopic Data-Driven Predictive Control
Alessio Russo, Alexandre Proutiere
We present a novel tube-based data-driven predictive control method for linear systems affected by a bounded addictive disturbance. Our method leverages recent results in the reach…