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» Parameterized Learning Complexity
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ACMSE
2010
ACM
15 years 23 hour ago
Learning to rank using 1-norm regularization and convex hull reduction
The ranking problem appears in many areas of study such as customer rating, social science, economics, and information retrieval. Ranking can be formulated as a classification pro...
Xiaofei Nan, Yixin Chen, Xin Dang, Dawn Wilkins
123
Voted
COGSCI
2011
85views more  COGSCI 2011»
15 years 53 min ago
Adaptation to Novel Accents: Feature-Based Learning of Context-Sensitive Phonological Regularities
This paper examines whether adults can adapt to novel accents of their native language that contain unfamiliar context-dependent phonological alternations. In two experiments, Fre...
Katrin Skoruppa, Sharon Peperkamp
COGSR
2011
105views more  COGSR 2011»
14 years 12 months ago
Inductive rule learning on the knowledge level
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...
Ute Schmid, Emanuel Kitzelmann
169
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JMLR
2010
143views more  JMLR 2010»
14 years 11 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
JMLR
2010
202views more  JMLR 2010»
14 years 11 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...