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» Evaluating algorithms that learn from data streams
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CORR
2008
Springer
143views Education» more  CORR 2008»
15 years 6 months ago
Join Bayes Nets: A new type of Bayes net for relational data
Many real-world data are maintained in relational format, with different tables storing information about entities and their links or relationships. The structure (schema) of the ...
Oliver Schulte, Hassan Khosravi, Flavia Moser, Mar...
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 8 months ago
Semi-Supervised Learning Based on Semiparametric Regularization
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
FOCS
1999
IEEE
15 years 11 months ago
Learning Mixtures of Gaussians
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Sanjoy Dasgupta
NLPRS
2001
Springer
15 years 11 months ago
Hierarchical Concept Description and Learning for Information Extraction
This paper addresses the problem of extracting information from textual documents, either normal documents or web pages. A new approach for extracting complicate information from ...
Luo Xiao, Dieter Wissmann, Michael Brown, Stefan J...
ICRA
2008
IEEE
191views Robotics» more  ICRA 2008»
16 years 1 months ago
Combining automated on-line segmentation and incremental clustering for whole body motions
Abstract— This paper describes a novel approach for incremental learning of human motion pattern primitives through on-line observation of human motion. The observed motion time ...
Dana Kulic, Wataru Takano, Yoshihiko Nakamura