Kernel functions are vital ingredients of several machine learning (ML) algorithms but often incur substantial memory and computational costs. We introduce an approach to kernel approximation in ML ...
The study of natural, social and technological phenomena in complex systems invariably requires approximations that coarse-grain and simplify, so that insights can be obtained about the causal ...
A large part of science and engineering work requires equations which model and analyze various situations. In many cases, these equations soon become complex and hard to resolve or solve analytically ...
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