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IJCNN
2006
IEEE
14 years 4 months ago
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
— We present a simple, intuitive argument based on “invariant imbedding” in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorith...
Eiji Mizutani, Stuart Dreyfus
GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
14 years 3 months ago
MILA - Multilevel Immune Learning Algorithm
The biological immune system is an intricate network of specialized tissues, organs, cells, and chemical molecules. T-cell-dependent humoral immune response is one of the complex i...
Dipankar Dasgupta, Senhua Yu, Nivedita Sumi Majumd...
JAIR
2002
120views more  JAIR 2002»
13 years 10 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
PERCOM
2005
ACM
14 years 4 months ago
Applying Active Space Principles to Active Classrooms
Recent developments in pervasive computing have enabled new features for collaboration and instrumentation in educational technology systems. An infrastructure for the integration...
Chad Peiper, David Warden, Ellick Chan, Roy H. Cam...
NN
2002
Springer
115views Neural Networks» more  NN 2002»
13 years 10 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow