139 search results - page 5 / 28 » On the Generalization Ability of On-Line Learning Algorithms |
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GECCO
2007
Springer
15 years 3 months ago
2007
Springer
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
HRI
2006
ACM
15 years 3 months ago
2006
ACM
The essence of the signal-to-symbol problem consists of associating a symbolic description of an object (e.g., a chair) to a signal (e.g., an image) that captures the real object....
AAAI
2008
14 years 12 months ago
2008
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
ML
1998
ACM
14 years 9 months ago
1998
ACM
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...