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ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
13 years 11 months ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti
AAAI
2008
13 years 7 months ago
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver
Conditional random field (CRF) is a popular graphical model for sequence labeling. The flexibility of CRF poses significant computational challenges for training. Using existing o...
Minmin Chen, Yixin Chen, Michael R. Brent
GECCO
2003
Springer
268views Optimization» more  GECCO 2003»
13 years 10 months ago
A Generalized Feedforward Neural Network Architecture and Its Training Using Two Stochastic Search Methods
Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks in which the synaptic interactions are mediated via a nonlinear mechanism called shuntin...
Abdesselam Bouzerdoum, Rainer Mueller
IJCNN
2000
IEEE
13 years 8 months ago
A Training Method with Small Computation for Classification
A training data selection method for multi-class data is proposed. This method can be used for multilayer neural networks (MLNN). The MLNN can be applied to pattern classification...
Kazuyuki Hara, Kenji Nakayama
EAAI
2006
123views more  EAAI 2006»
13 years 4 months ago
Imitation learning with spiking neural networks and real-world devices
This article is about a new approach in robotic learning systems. It provides a method to use a real-world device that operates in real-time, controlled through a simulated recurr...
Harald Burgsteiner