1921 search results - page 214 / 385 » Learning from sensor network data |
158
Voted
AROBOTS
2007
15 years 2 months ago
2007
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
106
Voted
ECSQARU
2005
Springer
15 years 8 months ago
2005
Springer
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
131
Voted
TNN
1998
15 years 2 months ago
1998
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
123
Voted
PKDD
2010
Springer
15 years 1 months ago
2010
Springer
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
135
Voted
FUZZIEEE
2007
IEEE
15 years 9 months ago
2007
IEEE
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...