1291 search results - page 107 / 259 » Learning Rules from Distributed Data |
120
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ICML
2004
IEEE
16 years 4 months ago
2004
IEEE
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
121
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NIPS
1994
15 years 4 months ago
1994
This paper discusses the linearly weighted combination of estimators in which the weighting functions are dependent on the input. We show that the weighting functions can be deriv...
151
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AAAI
2011
14 years 3 months ago
2011
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
124
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GECCO
2007
Springer
15 years 9 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
134
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COLING
1996
15 years 4 months ago
1996
We address the problem of automatically acquiring case frame patterns (selectional patterns) from large corpus data. In particular, we l)ropose a method of learning dependencies b...