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143
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JMLR
2012
13 years 5 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
ESANN
2006
15 years 4 months ago
Immune Network based Ensembles
This paper presents a new method for constructing ensembles of classifiers based on immune network theory, one of the most interesting paradigms within the field of artificial imm...
Nicolás García-Pedrajas, Colin Fyfe
127
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 3 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
JAIR
2008
157views more  JAIR 2008»
15 years 2 months ago
Learning to Reach Agreement in a Continuous Ultimatum Game
It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems nam...
Steven de Jong, Simon Uyttendaele, Karl Tuyls
NIPS
1990
15 years 3 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro