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Found 2 papers, 1 papers with code
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization
To tackle this challenge, we present a single-loop randomized stochastic algorithm, which requires updates for only a constant number of blocks at each iteration.
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence
To the best of our knowledge, this is the first time that stochastic algorithms are proposed to optimize NDCG with a provable convergence guarantee.
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