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Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms.

, , and . (2018)cite arxiv:1805.09717.

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Sparse Continuous Distributions and Fenchel-Young Losses., , , , , , and . CoRR, (2021)Learning with Differentiable Perturbed Optimizers., , , , , and . CoRR, (2020)Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion., , and . AISTATS, volume 33 of JMLR Workshop and Conference Proceedings, page 96-104. JMLR.org, (2014)SVD-Based Screening for the Graphical Lasso., , , , , , and . IJCAI, page 1682-1688. ijcai.org, (2017)Implicit differentiation of Lasso-type models for hyperparameter optimization., , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 810-821. PMLR, (2020)Scikit-learn: Machine Learning in Python., , , , , , , , , and 6 other author(s). J. Mach. Learn. Res., (2011)Routers in Vision Mixture of Experts: An Empirical Study., , , and . CoRR, (2024)Dual Gauss-Newton Directions for Deep Learning., and . CoRR, (2023)Efficient and Modular Implicit Differentiation., , , , , , , and . CoRR, (2021)Decoding-time Realignment of Language Models., , , , , , , , , and . CoRR, (2024)