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ENTITY Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms

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  1. RESEARCH · CL_128398 ·

    New algorithm tackles contaminated and heterogeneous multi-task learning

    Researchers have developed a new framework for contaminated multi-task learning, addressing challenges posed by data contamination and heterogeneity across tasks. The proposed method, a filtering-based robust multi-task…