Overview
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Explore kernel thinning and Stein thinning in this hour-long seminar presented by Lester Mackey from Microsoft and Stanford University. Delve into topics such as computational cardiology, inferential modeling, and distribution compression strategies. Learn about measuring approximation error, square root kernels, and the KernelSelfbalancing Hilbert Walk. Examine related work, practical applications, and results, including discussions on off-target sampling and kernel Stein discrepancy. Gain insights into Stein thinning terms and participate in a Q&A session to deepen your understanding of these advanced machine learning concepts.
Syllabus
Introduction
Computational cardiology
Inferential modeling
Distribution compression
Compression strategies
Problem set up
Measuring approximation error
Square root kernels
ktsplit
Kernel
Selfbalancing Hilbert Walk
Related Work
In Practice
Results
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Offtarget sampling
Kernel stein discrepancy
Stein thinning
Stein thinning terms
Summary
Questions
Taught by
Fields Institute