AAAI Publications, Twenty-First International Joint Conference on Artificial Intelligence

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Search Techniques for Fourier-Based Learning
Adam Drake, Dan Ventura

Last modified: 2009-06-26


Fourier-based learning algorithms rely on being able to efficiently find the large coefficients of a function's spectral representation. In this paper, we introduce and analyze techniques for finding large coefficients. We show how a previously introduced search technique can be generalized from the Boolean case to the real-valued case, and we apply it in branch-and-bound and beam search algorithms that have significant advantages over the best-first algorithm in which the technique was originally introduced.


spectral learning; fourier learning; search

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