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ICML
2008
IEEE
16 years 5 months ago
Memory bounded inference in topic models
What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
Ryan Gomes, Max Welling, Pietro Perona
IJCNN
2006
IEEE
15 years 10 months ago
Automated Model Selection (AMS) on Finite Mixtures: A Theoretical Analysis
— From the Bayesian Ying-Yang (BYY) harmony learning theory, a harmony function has been developed for finite mixtures with a novel property that its maximization can make model...
Jinwen Ma
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 5 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
134
Voted
RAS
2010
106views more  RAS 2010»
15 years 2 months ago
A developmental algorithm for ocular-motor coordination
This paper presents a model of ocular-motor development, inspired by ideas and data from developmental psychology. The learning problem concerns the growth of the transform betwee...
F. Chao, M. H. Lee, J. J. Lee
146
Voted
TNN
2008
178views more  TNN 2008»
15 years 4 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen