Talk by David Lopez-Paz (visitor from Ghahramani and Schölkopf's groups)

Speaker: David Lopez-Paz , University of Cambridge and MPI for Intelligent Systems

Date: Friday, December 13, 2013

Time: 1:00 PM to 2:00 PM Note: all times are in the Eastern Time Zone

Public: Yes

Location: G4 Lounge (Stata)

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Host: David Reshef, CSAIL

Contact: David Reshef,

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Reminder Subject: TALK: David Lopez-Paz (visitor from Ghahramani and Schölkopf groups)

Title: Using Randomness to Discover Patterns in the Large-Scale

Speaker: David Lopez-Paz, MPI for Intelligent Systems and University of Cambridge (

Abstract: The Random Projection method is quickly gaining popularity in the Machine Learning Community. Of special importance is the seminal work of Rahimi and Recht (2008), who showed that random non-linear features may be used in conjuction with linear models to perform tasks such as non-linear regression or classification. These randomized methods show great performance and robustness, while achieving dramatic computational savings.

I will introduce the Randomized Dependence Coefficient (RDC), a measure of non-linear dependence between random variables of arbitrary dimension based on the Hirschfeld-Gebelein-Renyi Maximum Correlation Coefficient. RDC is defined in terms of correlation of random non-linear copula features; it is invariant with respect to marginal distribution transformations, has low computational cost and is easy to implement: just five lines of R code.

Some unpublished results on Randomized Component Analysis (PCA, CCA) will be also presented.

Joint work with Philipp Hennig and Bernhard Schoelkopf.

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Created by David Reshef Email at Thursday, December 12, 2013 at 3:38 PM.