Boya Hou — accepted AI-conference papers

2023

Compressed Decentralized Learning of Conditional Mean Embedding Operators in Reproducing Kernel Hilbert Spaces

Boya Hou, Sina Sanjari, Nathan Dahlin, Subhonmesh Bose

AAAI 2023technical

Conditional mean embedding (CME) operators encode conditional probability densities within Reproducing Kernel Hilbert Space (RKHS). In this paper, we present a decentralized algorithm for a collection of agents to cooperatively approximate CME over a network. Communication constraints limit the agen…

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2023

Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach

Boya Hou, Sina Sanjari, Nathan Dahlin, Subhonmesh Bose, Umesh Vaidya

ICML 2023poster

Transfer operators provide a rich framework for representing the dynamics of very general, nonlinear dynamical systems. When interacting with reproducing kernel Hilbert spaces (RKHS), descriptions of dynamics often incur prohibitive data storage requirements, motivating dataset sparsification as a p…

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