4591 search results - page 180 / 919 » Learning from Dyadic Data |
120
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ICML
2000
IEEE
16 years 5 months ago
2000
IEEE
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
145
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RECOMB
2002
Springer
16 years 4 months ago
2002
Springer
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
182
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ESANN
2006
15 years 5 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
153
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ECCV
2008
Springer
16 years 6 months ago
2008
Springer
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application ...
143
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AAAI
2010
15 years 5 months ago
2010
Modeling human behavior requires vast quantities of accurately labeled training data, but for ubiquitous people-aware applications such data is rarely attainable. Even researchers...