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» Convergence of a Neural Network Classifier
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ML
2007
ACM
192views Machine Learning» more  ML 2007»
13 years 9 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
NN
2008
Springer
201views Neural Networks» more  NN 2008»
13 years 10 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
TNN
1998
132views more  TNN 1998»
13 years 9 months ago
Synthesis of fault-tolerant feedforward neural networks using minimax optimization
—In this paper we examine a technique by which fault tolerance can be embedded into a feedforward network leading to a network tolerant to the loss of a node and its associated w...
Dipti Deodhare, M. Vidyasagar, S. Sathiya Keerthi
KES
2008
Springer
13 years 10 months ago
Application of the Fuzzy Min-Max Neural Networks to Medical Diagnosis
In this paper, the Fuzzy Min-Max (FMM) neural network along with two modified FMM models are used for tackling medical diagnostic problems. The original FMM network establishes hyp...
Anas Quteishat, Chee Peng Lim
AAAI
1996
13 years 11 months ago
Constructive Neural Network Learning Algorithms
Constructive learning algorithms offer an attractive approach for the incremental construction of near-minimal neural-network architectures for pattern classification. They help ov...
Rajesh Parekh, Jihoon Yang, Vasant Honavar