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NPL
2006
109views more  NPL 2006»
15 years 4 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
DATE
2005
IEEE
150views Hardware» more  DATE 2005»
15 years 10 months ago
Pueblo: A Modern Pseudo-Boolean SAT Solver
This paper introduces a new SAT solver that integrates logicbased reasoning and integer programming methods to systems of CNF and PB constraints. Its novel features include an eff...
Hossein M. Sheini, Karem A. Sakallah
COLT
2010
Springer
15 years 2 months ago
The Convergence Rate of AdaBoost
Abstract. We pose the problem of determining the rate of convergence at which AdaBoost minimizes exponential loss. Boosting is the problem of combining many "weak," high-...
Robert E. Schapire
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 4 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
136
Voted
IJCNN
2006
IEEE
15 years 10 months ago
An Adaptive Penalty-Based Learning Extension for Backpropagation and its Variants
Abstract— Over the years, many improvements and refinements of the backpropagation learning algorithm have been reported. In this paper, a new adaptive penalty-based learning ex...
Boris Jansen, Kenji Nakayama