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SGAI
2007
Springer
15 years 5 months ago
Learning Sets of Sub-Models for Spatio-Temporal Prediction
In this paper we describe a novel technique which implements a spatiotemporal model as a set of sub-models based on first order logic. These sub-models model different, typicall...
Andrew Bennett, Derek R. Magee
DOCENG
2004
ACM
15 years 4 months ago
Supervised learning for the legacy document conversion
We consider the problem of document conversion from the renderingoriented HTML markup into a semantic-oriented XML annotation defined by user-specific DTDs or XML Schema descrip...
Boris Chidlovskii, Jérôme Fuselier
JMLR
2006
175views more  JMLR 2006»
14 years 11 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