70 search results - page 8 / 14 » Online and batch learning of pseudo-metrics |
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We show that several important Bayesian bounds studied in machine learning, both in the batch as well as the online setting, arise by an application of a simple compression lemma....
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
CVPR
2012
IEEE
12 years 26 days ago
2012
IEEE
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
ANNPR
2008
Springer
13 years 9 months ago
2008
Springer
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
ESANN
2003
13 years 9 months ago
2003
We derive continuous-time batch and online versions of the recently introduced efficient O(N2 ) training algorithm of Atiya and Parlos [2000] for fully recurrent networks. A mathem...