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20172024
most citedWeighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling

3 citations · 7 across the 13 of their papers we have counts for

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cs.LG2024

Investigating Regularization of Self-Play Language Models

Reda Alami, Abdalgader Abubaker, Mastane Achab +2

This paper explores the effects of various forms of regularization in the context of language model alignment via self-play. While both reinforcement learning from human feedback (…

cs.LG2023

A Risk-Averse Framework for Non-Stationary Stochastic Multi-Armed Bandits

Reda Alami, Mohammed Mahfoud, Mastane Achab

In a typical stochastic multi-armed bandit problem, the objective is often to maximize the expected sum of rewards over some time horizon . While the choice of a strategy that a…

cs.LG2023

Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study

Fouzi Boukhalfa, Reda Alami, Mastane Achab +2

In today's era, autonomous vehicles demand a safety level on par with aircraft. Taking a cue from the aerospace industry, which relies on redundancy to achieve high reliability, th…

cs.LG2023

One-Step Distributional Reinforcement Learning

Mastane Achab, Reda Alami, Yasser Abdelaziz Dahou Djilali +2

Reinforcement learning (RL) allows an agent interacting sequentially with an environment to maximize its long-term expected return. In the distributional RL (DistrRL) paradigm, the…

cs.LG2021

Robustness and risk management via distributional dynamic programming

Mastane Achab, Gergely Neu

In dynamic programming (DP) and reinforcement learning (RL), an agent learns to act optimally in terms of expected long-term return by sequentially interacting with its environment…