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JMLR
2006
175views more  JMLR 2006»
14 years 12 months ago
Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
We exploit the biconvex nature of the Euclidean non-negative matrix factorization (NMF) optimization problem to derive optimization schemes based on sequential quadratic and secon...
Matthias Heiler, Christoph Schnörr
ICMLA
2009
14 years 9 months ago
Learning Deep Neural Networks for High Dimensional Output Problems
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Benjamin Labbé, Romain Hérault, Cl&e...
JMLR
2010
149views more  JMLR 2010»
14 years 6 months ago
Fast Committee-Based Structure Learning
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
Ernest Mwebaze, John A. Quinn
ICPR
2008
IEEE
16 years 1 months ago
Supervised learning of a generative model for edge-weighted graphs
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...
Andrea Torsello, David L. Dowe
ICMCS
2006
IEEE
105views Multimedia» more  ICMCS 2006»
15 years 6 months ago
Web based Chinese Calligraphy Learning with 3-D Visualization Method
Chinese calligraphy is pictographic and each calligraphist has his own writing style. People often feel difficult in writing a demanded beautiful calligraphy style. In order to he...
Yingfei Wu, Yueting Zhuang, Yunhe Pan, Jiangqin Wu