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JMLR
2012
11 years 8 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
COLT
2006
Springer
13 years 10 months ago
The Rademacher Complexity of Linear Transformation Classes
Bounds are given for the empirical and expected Rademacher complexity of classes of linear transformations from a Hilbert space H to a ...nite dimensional space. The results imply ...
Andreas Maurer
JMLR
2012
11 years 8 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
FOCS
1996
IEEE
13 years 10 months ago
Learning Linear Transformations
Alan M. Frieze, Mark Jerrum, Ravi Kannan
ICASSP
2011
IEEE
12 years 10 months ago
Defining the controlling parameter in constrained discriminative linear transform for supervised speaker adaptation
Constrained discriminative linear transform (CDLT) optimized with Extended Baum-Welch (EBW) has been presented in the literature as a discriminative speaker adaptation method that...
Danning Jiang, Dimitri Kanevsky, Emmanuel Yashchin...