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Hypothesis Testing with Kernels

Szabo, Z; (2016) Hypothesis Testing with Kernels. Presented at: International Workshop on Pattern Recognition in Neuroimaging (PRNI), Trento, Italy. Green open access

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Abstract

In my talk, I am going to focus on two tasks: two-sample testing, and independence testing. In the first setting, we are given two sets of observations, and our goal is to check whether the two sets are statistically indistinguishable (this may be thought of as a generalization of a t-test). In the second setting, we have paired samples, and the goal is to determine whether they are independent (this generalizes the Pearson correlation test). Both tests are built around kernels, which are natural measures of similarity between objects, and have been developed for a very wide variety of domains. Thus, the tests apply to data as diverse as text, images, time series or graphs.

Type: Conference item (Presentation)
Title: Hypothesis Testing with Kernels
Event: International Workshop on Pattern Recognition in Neuroimaging (PRNI)
Location: Trento, Italy
Dates: 22 - 24 June 2016
Open access status: An open access version is available from UCL Discovery
Publisher version: http://prni2016.wix.com/prni2016
Language: English
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
URI: https://discovery.ucl.ac.uk/id/eprint/1476319
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