2615 search results - page 83 / 523 » Predictive Hebbian Learning |
144
Voted
ICML
2007
IEEE
16 years 4 months ago
2007
IEEE
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
122
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ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
109
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ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
113
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ICML
2005
IEEE
16 years 4 months ago
2005
IEEE
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
136
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ECML
2006
Springer
15 years 7 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...