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» An Effective Learning Method for Max-Min Neural Networks
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EH
2005
IEEE
158views Hardware» more  EH 2005»
15 years 9 months ago
Hardware Evolution of Analog Circuits for In-situ Robotic Fault-Recovery
We present a method for evolving and implementing artificial neural networks (ANNs) on Field Programmable Analog Arrays (FPAAs). These FPAAs offer the small size and low power usa...
Dmitry Berenson, Nicolás S. Estévez,...
158
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JMLR
2010
227views more  JMLR 2010»
15 years 2 months ago
PyBrain
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a vari...
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, M...
ACML
2009
Springer
15 years 10 months ago
Community Detection on Weighted Networks: A Variational Bayesian Method
Abstract. Massive real-world data are network-structured, such as social network, relationship between proteins and power grid. Discovering the latent communities is a useful way f...
Qixia Jiang, Yan Zhang, Maosong Sun
ESANN
2006
15 years 5 months ago
Evolino for recurrent support vector machines
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...
NIPS
2003
15 years 5 months ago
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks
Gradient-following learning methods can encounter problems of implementation in many applications, and stochastic variants are frequently used to overcome these difficulties. We ...
Justin Werfel, Xiaohui Xie, H. Sebastian Seung