210 search results - page 20 / 42 » Inference and Learning in Multi-dimensional Bayesian Network... |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
UAI
2003
13 years 8 months ago
2003
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
JMLR
2010
13 years 2 months ago
2010
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
NIPS
1998
13 years 8 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
HUC
2010
Springer
13 years 7 months ago
2010
Springer
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...