Sciweavers

277 search results - page 1 / 56
» Active Learning for Structure in Bayesian Networks
Sort
View
IJCAI
2001
15 years 9 days ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
PERCOM
2007
ACM
15 years 10 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
102
Voted
BIBE
2008
IEEE
111views Bioinformatics» more  BIBE 2008»
15 years 27 days ago
Structure learning for biomolecular pathways containing cycles
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
104
Voted
SARA
2007
Springer
15 years 5 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto
113
Voted
IFIP12
2008
15 years 10 days ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...