39 search results - page 4 / 8 » Selecting Features by Learning Markov Blankets |
AAAI
2007
13 years 9 months ago
2007
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
SDM
2009
SIAM
14 years 4 months ago
2009
SIAM
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
ICMLA
2009
13 years 5 months ago
2009
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
We address the feature selection problem for hidden Markov models (HMMs) in sequence classification. Temporal correlation in sequences often causes difficulty in applying featur...