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Malek khammassi

2 accepted papers

2026

Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning

ICML 2026spotlight

The family of linear recurrent neural networks has shown strong performance as recurrent memory units in partially observable reinforcement learning. We provide a theoretical justification for their empirical effectiveness by constructing and studying two linear filters: (i) the first exactly reprod…

Cited by 0SourceScholar
2025

Fundamental Social Learning Scaling Law for Tracking Hidden Markov Models

ICASSP 2025accepted

This paper studies the problem of interconnected agents collaborating to track a dynamic state from partially informative observations, where the dynamic state evolves according to a slowly varying finite-state Markov chain. Although the centralized version of this problem has been extensively studi…

Cited by 0SourceScholar