{"type":"ScholarlyArticle","title":"Search Techniques for Fourier-Based Learning","authors":[{"name":"Adam Drake","slug":"adam-drake","given":"Adam","family":"Drake","affiliation":""},{"name":"Dan Ventura","slug":"dan-ventura","given":"Dan","family":"Ventura","affiliation":""}],"abstract":"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.Adam Drake, Dan Ventura","doi":null,"url":"https://ijcai.org/proceedings/2009/176","pdf":"https://ijcai.org/proceedings/2009/0176.pdf","markdown":"https://ijcai.org/proceedings/2009/176.md","bibtex":"https://ijcai.org/proceedings/2009/bibtex/176","volume":{"slug":"2009","title":"Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2009","url":"https://ijcai.org/proceedings/2009/","year":2009,"location":"Pasadena, California, USA","dates":"","editors":"Hiroaki Kitano","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":176,"pages":{"first":1040,"last":1044},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}