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JMLR
2010
106views more  JMLR 2010»
14 years 6 months ago
Why Does Unsupervised Pre-training Help Deep Learning?
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...
CSUR
2006
135views more  CSUR 2006»
14 years 11 months ago
Adaptive information extraction
The growing availability of on-line textual sources and the potential number of applications of knowledge acquisition from textual data has lead to an increase in Information Extr...
Jordi Turmo, Alicia Ageno, Neus Català
JMLR
2006
206views more  JMLR 2006»
14 years 11 months ago
New Algorithms for Efficient High-Dimensional Nonparametric Classification
This paper is about non-approximate acceleration of high-dimensional nonparametric operations such as k nearest neighbor classifiers. We attempt to exploit the fact that even if w...
Ting Liu, Andrew W. Moore, Alexander G. Gray
IJCNN
2007
IEEE
15 years 6 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
SIGIR
2008
ACM
14 years 11 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff