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Št. zadetkov: 5
Video in druga učna gradiva
Oznake: computer science;machine learning;unsupervised learning
In recent work by (Song et al., 2007), it has been proposed to perform clustering by maximizing a Hilbert-Schmidt independence criterion with respect to a predefined cluster structure Y, by solving for the partition matrix. We extend this approach here to the case where the cluster structure Y is n ...
Leto: 2008 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;kernel methods
A number of important problems in signal processing depend on measures of statistical dependence. For instance, this dependence is minimised in the context of instantaneous ICA, in which linearly mixed signals are separated using their (assumed) pairwise independence from each other. A number of met ...
Leto: 2006 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;structured data
Given sets of observations of training and test data, we consider the problem of re-weighting the training data such that its distribution more closely matches that of the test data. We achieve this goal by matching covariate distributions between training and test sets in a high dimensional feature ...
Leto: 2009 Vir: videolectures.net
Video in druga učna gradiva
Oznake: events
Leto: 2007 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;transfer learning;multi-task learning
A method is presented for approximate Bayesian inference, where explicit models for the prior and likelihood are unknown (or difficult to compute), but sampling from these distributions is possbile. The method expresses the prior as an element in a reproducing kernel Hilbert space, and the likeliho ...
Leto: 2013 Vir: videolectures.net
Št. zadetkov: 5
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