1340 search results - page 210 / 268 » Structure learning of Bayesian networks using constraints |
175
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CIKM
2010
Springer
15 years 2 months ago
2010
Springer
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
164
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NN
2002
Springer
15 years 4 months ago
2002
Springer
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
165
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CVPR
2009
IEEE
17 years 2 days ago
2009
IEEE
In this paper we present a method for learning classspecific
features for recognition. Recently a greedy layerwise
procedure was proposed to initialize weights of deep
belief ne...
138
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CVPR
2007
IEEE
16 years 7 months ago
2007
IEEE
Several authors have noticed that the common representation of images as vectors is sub-optimal. The process of vectorization eliminates spatial relations between some of the near...
167
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NIPS
2004
15 years 6 months ago
2004
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...