1 citations · 1 across the 8 of their papers we have counts for
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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…