PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Fast Gaussian process methods for point process intensity estimation.
John P Cunningham, Krishna V Shenoy and Maneesh Sahani
In: ICML ’08: Proceedings of the 25th international conference on Machine learning (2008) Omni Press , Helsinki, Finland , pp. 192-199.

Abstract

Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attractive framework within which to infer underlying intensity functions. The result of this inference is a continuous function defined across time that is typically more amenable to analytical efforts. However, a naive implementation will become computationally infeasible in any problem of reasonable size, both in memory and run time requirements. We demonstrate problem specific methods for a class of renewal processes that eliminate the memory burden and reduce the solve time by orders of magnitude.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Brain Computer Interfaces
ID Code:5244
Deposited By:Maneesh Sahani
Deposited On:24 March 2009