1 citations · 1 across the 8 of their papers we have counts for
9 papers
Radial Tail Repair: Post-Training Correction for Diffusion and Flow Models
Hamza Cherkaoui, Hélène Halconruy, Antonio Ocello
Diffusion and flow-matching models may struggle to accurately represent distributional tails, especially for heavy-tailed data. Existing approaches often use heavy-tailed noise or…
Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training
Hamza Cherkaoui, Hélène Halconruy, Antonio Ocello
Recent works have proposed incorporating heavy-tailed (HT) noise into diffusion- and flow-based generative models, with the goals of better recovering the tails of target distribut…
When to Transfer: Adaptive Source Selection for Positive Transfer in Linear Models
Hamza Cherkaoui, Hélène Halconruy, Yohan Petetin
In many business settings, task-specific labeled data are scarce or costly to obtain, limiting supervised learning on a target task. A classical response is transfer learning (TL).…
Post-Training Corrections for Improved Time-Series Forecasting
Hamza Cherkaoui, Malik Tiomoko, Giuseppe Paolo +4
Time-series forecasting is a critical task in various business domains, but it remains inherently challenging. Typically, large forecasting models are trained in a single, resource…
High-Dimensional Analysis of Bootstrap Ensemble Classifiers
Malik Tiomoko, Hamza Cherkaoui, Mohamed El Amine Seddik +3
Bootstrap methods have long been the cornerstone of ensemble learning in machine learning. This paper presents a theoretical analysis of bootstrap techniques applied to the Least S…
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Giuseppe Paolo, Abdelhakim Benechehab, Hamza Cherkaoui +2
Hierarchical organization is fundamental to biological systems and human societies, yet artificial intelligence systems often rely on monolithic architectures that limit adaptabili…
Kolb-Based Experiential Learning for Generalist Agents with Human-Level Kaggle Data Science Performance
Antoine Grosnit, Alexandre Maraval, Refinath S N +16
Human expertise emerges through iterative cycles of interaction, reflection, and internal model updating, which are central to cognitive theories such as Kolb's experiential learni…
Price of Safety in Linear Best Arm Identification
Xuedong Shang, Igor Colin, Merwan Barlier +1
We introduce the safe best-arm identification framework with linear feedback, where the agent is subject to some stage-wise safety constraint that linearly depends on an unknown pa…
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
The multi-agent linear bandit setting is a well-known setting for which designing efficient collaboration between agents remains challenging. This paper studies the impact of data…