Uniform Convergence Rates for Lipschitz Learning Down to Graph Connectivity
berkeley.edu
Uniform Convergence Rates for Lipschitz Learning Down to Graph Connectivity
The last few years have seen a deluge of discrete to continuum convergence results for various problems in graph-based learning. This theory makes connections between discrete machine learning and continuum partial differential equations or variational problems, leading to new insights and better algorithms.
Oct 26, 2021
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