602 citations · 2.9k across the 103 of their papers we have counts for
3 papers · 2 filters
Kernel Dependence Network
Chieh Wu, Aria Masoomi, Arthur Gretton +1
We propose a greedy strategy to spectrally train a deep network for multi-class classification. Each layer is defined as a composition of linear weights with the feature map of a G…
Learning Deep Features in Instrumental Variable Regression
Liyuan Xu, Yutian Chen, Siddarth Srinivasan +3
Instrumental variable (IV) regression is a standard strategy for learning causal relationships between confounded treatment and outcome variables from observational data by utilizi…
Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar +1
A novel optimization approach is proposed for application to policy gradient methods and evolution strategies for reinforcement learning (RL). The procedure uses a computationally…