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NIPS
2000
15 years 19 days ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
ESWA
2006
154views more  ESWA 2006»
14 years 11 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim
INFORMATICALT
2000
118views more  INFORMATICALT 2000»
14 years 11 months ago
Hexagonal Approach and Modeling for the Visual Cortex
In this paper, the hexagonal approach was proposed for modeling the functioning of cerebral cortex, especially, the processes of learning and recognition of visual information. Thi...
Algis Garliauskas, Alvydas Soliunas
94
Voted
ML
2007
ACM
122views Machine Learning» more  ML 2007»
14 years 10 months ago
Status report: hot pickles, and how to serve them
The need for flexible forms of serialisation arises under many circumstances, e.g. for doing high-level inter-process communication or to achieve persistence. Many languages, inc...
Andreas Rossberg, Guido Tack, Leif Kornstaedt
ML
2007
ACM
192views Machine Learning» more  ML 2007»
14 years 10 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang