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» Machine Learning with Data Dependent Hypothesis Classes
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ACL
2006
13 years 10 months ago
Discriminative Classifiers for Deterministic Dependency Parsing
Deterministic parsing guided by treebankinduced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. We present a systemat...
Johan Hall, Joakim Nivre, Jens Nilsson
ICML
2010
IEEE
13 years 9 months ago
OTL: A Framework of Online Transfer Learning
In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Peilin Zhao, Steven C. H. Hoi
IJON
2011
169views more  IJON 2011»
13 years 3 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...
ALT
2008
Springer
14 years 5 months ago
Learning with Temporary Memory
In the inductive inference framework of learning in the limit, a variation of the bounded example memory (Bem) language learning model is considered. Intuitively, the new model con...
Steffen Lange, Samuel E. Moelius, Sandra Zilles
COLT
2006
Springer
14 years 13 days ago
Memory-Limited U-Shaped Learning
U-shaped learning is a learning behaviour in which the learner first learns a given target behaviour, then unlearns it and finally relearns it. Such a behaviour, observed by psych...
Lorenzo Carlucci, John Case, Sanjay Jain, Frank St...