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A Modern Take on the Bias-Variance Tradeoff in Neural Networks., , , , , , and . CoRR, (2018)A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method, , and . CoRR, (2012)A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 2863-2873. PMLR, (2020)On the Convergence of Continuous Constrained Optimization for Structure Learning., , , and . CoRR, (2020)Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods., , and . J. Mach. Learn. Res., (2018)Bayesian Structure Learning with Generative Flow Networks, , , , , , and . arXiv preprint arXiv:2202.13903, (2022)SVRG meets AdaGrad: painless variance reduction., , , , and . Mach. Learn., 111 (12): 4359-4409 (2022)PopulAtion Parameter Averaging (PAPA)., , , , and . CoRR, (2023)Geometry-Aware Universal Mirror-Prox., and . CoRR, (2020)Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies., , , , , , and . CoRR, (2024)