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FeDXL: Provable Federated Learning for Deep X-Risk Optimization., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 11934-11966. PMLR, (2023)A Practical Online Method for Distributionally Deep Robust Optimization., , , , and . CoRR, (2020)Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity., , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 12219-12229. PMLR, (2021)Revisiting SGD with Increasingly Weighted Averaging: Optimization and Generalization Perspectives., , , , and . CoRR, (2020)Accelerating Deep Learning with Millions of Classes., , , , and . ECCV (23), volume 12368 of Lecture Notes in Computer Science, page 711-726. Springer, (2020)On Stochastic Moving-Average Estimators for Non-Convex Optimization., , , , and . CoRR, (2021)Research on Cultivation of Innovation and Entrepreneurship Ability of Applied Talents under the Concept of "New Engineering"., , and . CIPAE, page 757-759. ACM, (2021)Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks., , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 3864-3874. PMLR, (2020)Compositional Training for End-to-End Deep AUC Maximization., , , and . ICLR, OpenReview.net, (2022)Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 13550-13583. PMLR, (2023)