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» Learning from labeled and unlabeled data on a directed graph
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ICML
2004
IEEE
16 years 19 days ago
Co-EM support vector learning
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...
Ulf Brefeld, Tobias Scheffer
ICML
2009
IEEE
16 years 19 days ago
Unsupervised hierarchical modeling of locomotion styles
This paper describes an unsupervised learning technique for modeling human locomotion styles, such as distinct related activities (e.g. running and striding) or variations of the ...
Wei Pan, Lorenzo Torresani
COGSCI
2002
99views more  COGSCI 2002»
14 years 11 months ago
Learning words from sights and sounds: a computational model
This paper presents an implemented computational model of word acquisition which learns directly from raw multimodal sensory input. Set in an information theoretic framework, the ...
Deb Roy, Alex Pentland
LREC
2008
89views Education» more  LREC 2008»
15 years 1 months ago
Parser Evaluation and the BNC: Evaluating 4 constituency parsers with 3 metrics
We evaluate discriminative parse reranking and parser self-training on a new English test set using four versions of the Charniak parser and a variety of parser evaluation metrics...
Jennifer Foster, Josef van Genabith
NIPS
2004
15 years 1 months ago
Active Learning for Anomaly and Rare-Category Detection
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Dan Pelleg, Andrew W. Moore