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Implicit differentiation of Lasso-type models for hyperparameter optimization.

, , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 810-821. PMLR, (2020)

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Sparse and Smooth: improved guarantees for Spectral Clustering in the Dynamic Stochastic Block Model., and . CoRR, (2020)Implicit differentiation of Lasso-type models for hyperparameter optimization., , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 810-821. PMLR, (2020)Implicit differentiation for fast hyperparameter selection in non-smooth convex learning., , , , , , and . CoRR, (2021)Automatic differentiation of nonsmooth iterative algorithms., , and . NeurIPS, (2022)A framework for bilevel optimization that enables stochastic and global variance reduction algorithms., , , and . NeurIPS, (2022)Automated Data-Driven Selection of the Hyperparameters for Total-Variation-Based Texture Segmentation., , , and . J. Math. Imaging Vis., 63 (7): 923-952 (2021)A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 82-90. PMLR, (2024)Derivatives of Stochastic Gradient Descent., , and . CoRR, (2024)A Near-Optimal Algorithm for Bilevel Empirical Risk Minimization., , , and . CoRR, (2023)Refitting Solutions Promoted by ℓ _12 Sparse Analysis Regularizations with Block Penalties., , , and . SSVM, volume 11603 of Lecture Notes in Computer Science, page 131-143. Springer, (2019)