7.4k citations · 28.3k across the 205 of their papers we have counts for
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Feature Robust Optimal Transport for High-dimensional Data
Mathis Petrovich, Chao Liang, Ryoma Sato +6
Optimal transport is a machine learning problem with applications including distribution comparison, feature selection, and generative adversarial networks. In this paper, we propo…
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport
Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai +3
Estimating mutual information is an important statistics and machine learning problem. To estimate the mutual information from data, a common practice is preparing a set of paired…
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network?
Simon S. Du, Yining Wang, Xiyu Zhai +3
It is widely believed that the practical success of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) owes to the fact that CNNs and RNNs use a more compact…
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai +3
Measuring divergence between two distributions is essential in machine learning and statistics and has various applications including binary classification, change point detection,…
Transformation Autoregressive Networks
Junier B. Oliva, Avinava Dubey, Manzil Zaheer +4
The fundamental task of general density estimation has been of keen interest to machine learning. In this work, we attempt to systematically characterize methods for density…
Stochastic Variational Deep Kernel Learning
Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov +1
Deep kernel learning combines the non-parametric flexibility of kernel methods with the inductive biases of deep learning architectures. We propose a novel deep kernel learning mod…