Titlebook: Artificial Neural Networks - ICANN 2006; 16th International C Stefanos D. Kollias,Andreas Stafylopatis,Erkki Oja Conference proceedings 200

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hangdog

AXIOM

Speeding Up the Wrapper Feature Subset Selection in Regression by Mutual Information Relevance and Rancy filter using mutual information between regression and target variables. We introduce permutation tests to find statistically significant relevant and redundant features. Second, a wrapper searches for good candidate feature subsets by taking the regression model into account. The advantage of

Glaci冰

Visual-Acuity

Comparative Investigation on Dimension Reduction and Regression in Three Layer Feed-Forward Neural Nd as taking the role of feature extraction and dimension reduction, and that the regression performance relies on how the feature dimension or equivalently the number of hidden units is determined appropriately. There are many publications on determining the hidden unit number for a desired generali

Increment

On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recogic plasticity and changes in the network structure. Event driven computation optimizes processing speed in order to simulate networks with large number of neurons. The training procedure is applied to the face recognition task. Preliminary experiments on a public available face image dataset show th

甜食

Learning Long Term Dependencies with Recurrent Neural Networksntify long-term dependencies in the data. Especially when they are trained with backpropagation through time (BPTT) it is claimed that RNNs unfolded in time fail to learn inter-temporal influences more than ten time steps apart..This paper provides a disproof of this often cited statement. We show t

絕緣

Adaptive On-Line Neural Network Retraining for Real Life Multimodal Emotion Recognitionadvances have been made in unimodal speech and video emotion analysis where facial expression information and prosodic audio features are treated independently. The need however to combine the two modalities in a naturalistic context, where adaptation to specific human characteristics and expressivi

Debrief

Time Window Width Influence on Dynamic BPTT(h) Learning Algorithm Performances: Experimental Studyme BPTT(h) learning algorithms. Statistical experiments based on the identification of a real biped robot balancing mechanism are carried out to raise the link between the window width and the stability, the speed and the accuracy of the learning. The time window width choice is shown to be crucial

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