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Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions.

, , , , and . ICLR (Poster), OpenReview.net, (2019)

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On Monotonic Linear Interpolation of Neural Network Parameters., , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 7168-7179. PMLR, (2021)Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix., and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 2304-2313. JMLR.org, (2015)Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure., , , , , and . ICLR (Workshop), OpenReview.net, (2018)Noisy Natural Gradient as Variational Inference., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5847-5856. PMLR, (2018)Automatic Construction and Natural-Language Description of Nonparametric Regression Models., , , , and . AAAI, page 1242-1250. AAAI Press, (2014)Path Independent Equilibrium Models Can Better Exploit Test-Time Computation., , , , , , , and . NeurIPS, (2022)Isolating Sources of Disentanglement in Variational Autoencoders., , , and . NeurIPS, page 2615-2625. (2018)Learning Wake-Sleep Recurrent Attention Models., , , and . NIPS, page 2593-2601. (2015)Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model., , , , , , , and . NeurIPS, page 8194-8205. (2019)Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks., , and . NeurIPS, page 8080-8091. (2019)