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Found 2 papers, 1 papers with code
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.
Bayesian Online Prediction of Change Points
Online detection of instantaneous changes in the generative process of a data sequence generally focuses on retrospective inference of such change points without considering their future occurrences.
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