7 papers · 1 filter
LLMs as Feature Engineers for Text-and-Tabular Prediction
Merwan Barlier, Blaz Skrlj
We introduce an iterative framework that automates the extraction of interpretable, schema-bound categorical features from unstructured text for tabular prediction models. To navig…
Building a User Foundation Model for the Open Web
Solal Vernier, Ivan Can Arisoy, Merwan Barlier +1
User foundation models have demonstrated strong results in e-commerce and social recommendation, but most industrial deployments assume environments where user identity is stable a…
Differentially Private Policy Gradient
Alexandre Rio, Merwan Barlier, Igor Colin
Motivated by the increasing deployment of reinforcement learning in the real world, involving a large consumption of personal data, we introduce a differentially private (DP) polic…
Enhancing Reinforcement Learning Agents with Local Guides
Paul Daoudi, Bogdan Robu, Christophe Prieur +2
This paper addresses the problem of integrating local guide policies into a Reinforcement Learning agent. For this, we show how to adapt existing algorithms to this setting before…
Differentially Private Deep Model-Based Reinforcement Learning
Alexandre Rio, Merwan Barlier, Igor Colin +1
We address private deep offline reinforcement learning (RL), where the goal is to train a policy on standard control tasks that is differentially private (DP) with respect to indiv…
A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning
Paul Daoudi, Christophe Prieur, Bogdan Robu +2
Off-dynamics Reinforcement Learning (ODRL) seeks to transfer a policy from a source environment to a target environment characterized by distinct yet similar dynamics. In this cont…