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ADCM
2008
136views more  ADCM 2008»
13 years 9 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
TABLEAUX
1998
Springer
14 years 1 months ago
The FaCT System
The FaCT (Fact and Concept Training) System provides a general platform for delivering practice in the form of discrete flashcard-like drills. The system optimizes practice schedu...
Ian Horrocks
DAGSTUHL
2007
13 years 10 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
14 years 9 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith