70 search results - page 6 / 14 » Bottom-Up Learning of Markov Network Structure |
PERCOM
2003
ACM
14 years 29 days ago
2003
ACM
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring suppor...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
GECCO
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. Factored Markov Decision Processes is the theoretical framework underlying multi-step Learning Classifier Systems research. This framework is mostly used in the context ...
JMLR
2008
13 years 7 months ago
2008
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
KDD
2003
ACM
14 years 8 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...