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» Constructive Neural Network Learning Algorithms
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IJCNN
2006
IEEE
15 years 8 months ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh
105
Voted
GECCO
2005
Springer
204views Optimization» more  GECCO 2005»
15 years 7 months ago
Modeling systems with internal state using evolino
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Daan Wierstra, Faustino J. Gomez, Jürgen Schm...
125
Voted
WWW
2004
ACM
16 years 3 months ago
Learning block importance models for web pages
Some previous works show that a web page can be partitioned to multiple segments or blocks, and usually the importance of those blocks in a page is not equivalent. Also, it is pro...
Ruihua Song, Haifeng Liu, Ji-Rong Wen, Wei-Ying Ma
NPL
1998
175views more  NPL 1998»
15 years 1 months ago
Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network
Abstract. One of the main problems associated with arti cial neural networks online learning methods is the estimation of model order. In this paper, we report about a new approach...
Roman Rosipal, Milos Koska, Igor Farkas
101
Voted
CEC
2008
IEEE
15 years 8 months ago
Neuro-evolving maintain-station behavior for realistically simulated boats
— We evolve a neural network controller for a boat that learns to maintain a given bearing and range with respect to a moving target in the Lagoon 3D game environment. Simulating...
Nathan A. Penrod, David Carr, Sushil J. Louis, Bob...