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Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate Analysis
We propose the particle dual averaging (PDA) method, which generalizes t...
12/31/2020 ∙ by Atsushi Nitanda, et al. ∙
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When Does Preconditioning Help or Hurt Generalization?
While second order optimizers such as natural gradient descent (NGD) oft...
06/18/2020 ∙ by Shun-ichi Amari, et al. ∙
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On the Optimal Weighted ℓ_2 Regularization in Overparameterized Linear Regression
We consider the linear model 𝐲 = 𝐗β_⋆ + ϵ with 𝐗∈ℝ^n× p in the overparam...
06/10/2020 ∙ by Denny Wu, et al. ∙
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Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Sampling with Markov chain Monte Carlo methods typically amounts to disc...
06/19/2019 ∙ by Xuechen Li, et al. ∙
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Modeling the Biological Pathology Continuum with HSIC-regularized Wasserstein Auto-encoders
A crucial challenge in image-based modeling of biomedical data is to ide...
01/20/2019 ∙ by Denny Wu, et al. ∙
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Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
Measuring divergence between two distributions is essential in machine l...
02/17/2018 ∙ by Makoto Yamada, et al. ∙
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Selecting the Best in GANs Family: a Post Selection Inference Framework
"Which Generative Adversarial Networks (GANs) generates the most plausib...
02/15/2018 ∙ by Yao-Hung Hubert Tsai, et al. ∙
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"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study
Recent works investigated the generalization properties in deep neural n...
02/15/2018 ∙ by Denny Wu, et al. ∙
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