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NIPS
2000
13 years 8 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
ICANN
2009
Springer
14 years 1 months ago
Learning Features by Contrasting Natural Images with Noise
Abstract. Modeling the statistical structure of natural images is interesting for reasons related to neuroscience as well as engineering. Currently, this modeling relies heavily on...
Michael Gutmann, Aapo Hyvärinen
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
14 years 1 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson
NN
2007
Springer
112views Neural Networks» more  NN 2007»
13 years 6 months ago
An augmented CRTRL for complex-valued recurrent neural networks
Real world processes with an “intensity” and “direction” component can be made complex by convenience of representation (vector fields, radar, sonar), and their processin...
Su Lee Goh, Danilo P. Mandic
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 7 months ago
On the effects of node duplication and connection-oriented constructivism in neural XCSF
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
Gerard David Howard, Larry Bull