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Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark
This method aims to mitigate forgetting while adapting to new classes and domain shifts by combining the advantages of the Replay and Pseudo-Label methods and solving their limitations in the proposed scenario.
A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility Services
As Machine Learning systems become increasingly popular across diverse application domains, including those with direct human implications, the imperative of equity and algorithmic fairness has risen to prominence in the Artificial Intelligence community.
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