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NPL
2006
109views more  NPL 2006»
13 years 7 months ago
CB3: An Adaptive Error Function for Backpropagation Training
Effective backpropagation training of multi-layer perceptrons depends on the incorporation of an appropriate error or objective function. Classification-based (CB) error functions ...
Michael Rimer, Tony Martinez
ICANN
2009
Springer
14 years 2 months ago
Adaptive Feature Transformation for Image Data from Non-stationary Processes
Abstract. This paper introduces the application of the feature transformation approach proposed by Torkkola [1] to the domain of image processing. Thereto, we extended the approach...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...
IWANN
1999
Springer
14 years 1 days ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
WIOPT
2011
IEEE
12 years 11 months ago
Distributed function computation in networks: A joint delay-energy perspective
Abstract—This paper considers the following network computation problem:
Nikhil Karamchandani, Massimo Franceschetti
ECIR
2011
Springer
12 years 11 months ago
Weight-Based Boosting Model for Cross-Domain Relevance Ranking Adaptation
Adaptation techniques based on importance weighting were shown effective for RankSVM and RankNet, viz., each training instance is assigned a target weight denoting its importance ...
Peng Cai, Wei Gao, Kam-Fai Wong, Aoying Zhou