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» Neural Learning from Unbalanced Data Using Noise Modeling
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ICANN
2005
Springer
14 years 2 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
IJCAI
1989
13 years 10 months ago
Integrating Knowledge-Based System and Neural Network Techniques for Robotic Skill Acquisition
This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...
David Handelman, Stephen Lane, Jack Gelfand
NIPS
2003
13 years 10 months ago
Ambiguous Model Learning Made Unambiguous with 1/f Priors
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Gurinder S. Atwal, William Bialek
RSFDGRC
2005
Springer
14 years 2 months ago
Intelligent Algorithms for Optical Track Audio Restoration
Abstract. The Unpredictability Measure computation algorithm applied to psychoacoustic model-based broadband noise attenuation is discussed. A learning decision algorithm based on ...
Andrzej Czyzewski, Marek Dziubinski, Lukasz Litwic...
BMCBI
2004
133views more  BMCBI 2004»
13 years 8 months ago
Artificial neural network approach for selection of susceptible single nucleotide polymorphisms and construction of prediction m
Background: Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have pre...
Yasuyuki Tomita, Shuta Tomida, Yuko Hasegawa, Yoic...