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Muhammad Aneeq Uz Zaman

2 accepted papers

2025

Regularized Domain Adaptation for Estimation Tasks in Partially Observed Target Domains

ICASSP 2025accepted

The performance of machine learning algorithms is limited by the availability of training data. Transfer learning can alleviate this limitation by adapting models trained in data-rich domains to a data-sparse domain. In this work, we propose a method for data augmentation in a partially sampled data…

Cited by 0SourceScholar
2023

Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path

AISTATS 2023poster

We consider online reinforcement learning in Mean-Field Games (MFGs). Unlike traditional approaches, we alleviate the need for a mean-field oracle by developing an algorithm that approximates the Mean-Field Equilibrium (MFE) using the single sample path of the generic agent. We call this Sandbox Lea…

Cited by 31SourcePDFScholar