Efficient Machine Learning using Random Projections
published: Dec. 29, 2007, recorded: December 2007, views: 5955
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
As an alternative to cumbersome nonlinear schemes for dimensionality reduction, the technique of random linear projection has recently emerged as a viable alternative for storage and rudimentary processing of high-dimensional data. We invoke new theory to motivate the following claim: the random projection method may be used in conjunction with standard algorithms for a multitude of machine learning tasks, with virtually no degradation in performance. Thus, random projections can been shown to result in both significant computational savings and provably good performance.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !