UCL ELLIS

Speaker	Dimitrios Athanasakis
Affiliation	UCL
Date	Friday, 11 April 2014
Time	13:00-14:00
Location	Zoom
Link	Malet Place Engineering 1.03
Event series	DeepMind/ELLIS CSML Seminar Series
Abstract	Following recent work in non-linear feature selection we propose a novel method for assessing the contribution of a feature through estimating its expected impact on the alignment or HSIC measure. Theoretical analysis of this approach is included showing that for appropriate polynomial sample sizes influential features can be distinguished from irrelevant ones. We present experimental evidence which confirm the analysis including applications in representation learning. The method was used to obtain a 3rd position result in the 2013 ICML black box learning challenge, as well as competitive results in signal peptide prediction, an important bioinformatics application.
Biography