Search Results for author:
Found 4 papers, 2 papers with code
Estimation Beyond Data Reweighting: Kernel Method of Moments
We provide a variant of our estimator for conditional moment restrictions and show that it is asymptotically first-order optimal for such problems.
Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control
We provide a functional view of distributional robustness motivated by robust statistics and functional analysis.
Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics
Random features is a powerful universal function approximator that inherits the theoretical rigor of kernel methods and can scale up to modern learning tasks.
Adversarially Robust Kernel Smoothing
We propose a scalable robust learning algorithm combining kernel smoothing and robust optimization.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
