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JMLR
2010
91views more  JMLR 2010»
13 years 3 days ago
Composite Binary Losses
We study losses for binary classification and class probability estimation and extend the understanding of them from margin losses to general composite losses which are the compos...
Mark D. Reid, Robert C. Williamson
JMLR
2010
206views more  JMLR 2010»
13 years 3 days ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
JMLR
2010
146views more  JMLR 2010»
13 years 3 days ago
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking
The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical p...
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhar...
JMLR
2012
11 years 7 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey
COLT
2010
Springer
13 years 3 months ago
Efficient Classification for Metric Data
Recent advances in large-margin classification of data residing in general metric spaces (rather than Hilbert spaces) enable classification under various natural metrics, such as ...
Lee-Ad Gottlieb, Leonid Kontorovich, Robert Krauth...