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Online Learning Rate Adaptation with Hypergradient Descent.

, , , , и . ICLR (Poster), OpenReview.net, (2018)

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Mark Schmidt

Mark Schmidt

Mark Schmidt

Mark Schmidt

Mark Schmidt

 

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Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent., , и . CoRR, (2020)Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron., , и . CoRR, (2018)Target-based Surrogates for Stochastic Optimization., , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 18614-18651. PMLR, (2023)Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent., , и . AISTATS, том 130 из Proceedings of Machine Learning Research, стр. 3295-3303. PMLR, (2021)A Less Biased Evaluation of Out-of-distribution Sample Detectors., , и . BMVC, стр. 3. BMVA Press, (2019)Where are the Masks: Instance Segmentation with Image-level Supervision., , и . BMVC, стр. 255. BMVA Press, (2019)Where Are the Blobs: Counting by Localization with Point Supervision., , , , и . ECCV (2), том 11206 из Lecture Notes in Computer Science, стр. 560-576. Springer, (2018)Combining Bayesian Optimization and Lipschitz Optimization., , и . CoRR, (2018)Structured second-order methods via natural gradient descent., , , и . CoRR, (2021)Segmenting brain tumors using alignment-based features., , , , и . ICMLA, IEEE Computer Society, (2005)