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Convergence rates for pretraining and dropout: Guiding learning parameters using network structure.

, , and . CoRR, (2015)

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Speeding up Permutation Testing in Neuroimaging., , , , and . CoRR, (2015)When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications., , , , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 4170-4179. PMLR, (2017)Experimental Design on a Budget for Sparse Linear Models and Applications., , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 583-592. JMLR.org, (2016)On the interplay of network structure and gradient convergence in deep learning., , and . CoRR, (2015)Convergence of gradient based pre-training in Denoising autoencoders., , and . CoRR, (2015)Randomized Denoising Autoencoders for Smaller and Efficient Imaging Based AD Clinical Trials., , , and . MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 470-478. Springer, (2014)Continual self-training with bootstrapped remixing for speech enhancement., , , , and . CoRR, (2021)Learning to Personalize Equalization for High-Fidelity Spatial Audio Reproduction., , , , , and . ICASSP, page 1-5. IEEE, (2023)On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation., , and . CoRR, (2017)Speeding up Permutation Testing in Neuroimaging., , , , and . NIPS, page 890-898. (2013)