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» Generation of Attributes for Learning Algorithms
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ICML
2007
IEEE
14 years 9 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
ICML
2005
IEEE
14 years 9 months ago
Learning predictive representations from a history
Predictive State Representations (PSRs) have shown a great deal of promise as an alternative to Markov models. However, learning a PSR from a single stream of data generated from ...
Eric Wiewiora
ACL
2009
13 years 6 months ago
Automatically Generating Wikipedia Articles: A Structure-Aware Approach
In this paper, we investigate an approach for creating a comprehensive textual overview of a subject composed of information drawn from the Internet. We use the high-level structu...
Christina Sauper, Regina Barzilay
ICML
2009
IEEE
14 years 3 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
COLT
1998
Springer
14 years 1 months ago
Learning One-Variable Pattern Languages in Linear Average Time
A new algorithm for learning one-variable pattern languages is proposed and analyzed with respect to its average-case behavior. We consider the total learning time that takes into...
Rüdiger Reischuk, Thomas Zeugmann