The rise of the search engine as a major tool for searches on the internet has spawned a large and growing industry that has changed modern commerce, education, and the study of scientific, financial, and social data bases. The underpinnings of these search engines are mathematical algorithms which are well adapted to large and rapid computations, mainly from linear algebra. While the impact of this industry has been enormous, there is a parallel development in the applications of these methods to other related problems concerning the extraction of knowledge from large databases. This long program at IPAM will be devoted to new mathematics and methodologies of knowledge engines: the mathematical procedures used to extract knowledge from large databases. While this includes topics related to search engines it is mainly devoted to the more general problem of finding features in a database or using defined features to search within a database. It is expected that this program will be of interest to a large number of scientific fields, including pure and applied mathematics, statistics, bioinformatics, and engineering. We also anticipate the study of applications to finance, the social sciences, and the humanities. Some of the topics to be investigated are listed below:
Ronald Coifman
(Yale University)
Yuval Kluger
(New York University)
Yann LeCun
(New York University)
Vladimir Rokhlin
(Yale University)
Karin Verspoor
(Los Alamos National Laboratory)