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» Convergent design of piecewise linear neural networks
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FLAIRS
2004
13 years 9 months ago
Iterative Improvement of Neural Classifiers
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
ICPADS
2006
IEEE
14 years 1 months ago
Fast Convergence in Self-Stabilizing Wireless Networks
The advent of large scale multi-hop wireless networks highlights problems of fault tolerance and scale in distributed system, motivating designs that autonomously recover from tra...
Nathalie Mitton, Eric Fleury, Isabelle Guér...
JMLR
2006
389views more  JMLR 2006»
13 years 7 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
TIT
2010
141views Education» more  TIT 2010»
13 years 2 months ago
Distributed averaging via lifted Markov chains
Abstract--Motivated by applications of distributed linear estimation, distributed control, and distributed optimization, we consider the question of designing linear iterative algo...
Kyomin Jung, Devavrat Shah, Jinwoo Shin
SIAMJO
2011
13 years 2 months ago
A Unifying Polyhedral Approximation Framework for Convex Optimization
Abstract. We propose a unifying framework for polyhedral approximation in convex optimization. It subsumes classical methods, such as cutting plane and simplicial decomposition, bu...
Dimitri P. Bertsekas, Huizhen Yu