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» Learning Generative Models with the Up-Propagation Algorithm
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ICML
2009
IEEE
14 years 2 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
GECCO
2007
Springer
532views Optimization» more  GECCO 2007»
14 years 1 months ago
Evolving evolutionary algorithms using evolutionary algorithms
A new model for automatic generation of Evolutionary Algorithms (EAs) by evolutionary means is proposed in this paper. The model is based on a simple Genetic Algorithm (GA). Every...
Laura Diosan, Mihai Oltean
GEOINFO
2007
13 years 9 months ago
Comparison of Machine Learning Algorithms for Mapping the Phytophysiognomies of the Brazilian Cerrado
This present work describes the classification of the Phytophysiognomies present in the Brazilian Cerrado biome through the means Artificial Intelligence; data from remote sensing ...
Luciano T. de Oliveira, Thomaz C. de A. Oliveira, ...
ECML
2005
Springer
14 years 1 months ago
Multi-view Discriminative Sequential Learning
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
Ulf Brefeld, Christoph Büscher, Tobias Scheff...
TOIS
2010
128views more  TOIS 2010»
13 years 6 months ago
Learning author-topic models from text corpora
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...