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ICML
2004
IEEE
14 years 9 months ago
A hierarchical method for multi-class support vector machines
We introduce a framework, which we call Divide-by-2 (DB2), for extending support vector machines (SVM) to multi-class problems. DB2 offers an alternative to the standard one-again...
Volkan Vural, Jennifer G. Dy
NIPS
2008
13 years 10 months ago
A Scalable Hierarchical Distributed Language Model
Neural probabilistic language models (NPLMs) have been shown to be competitive with and occasionally superior to the widely-used n-gram language models. The main drawback of NPLMs...
Andriy Mnih, Geoffrey E. Hinton
ECML
2006
Springer
14 years 18 days ago
Improving Control-Knowledge Acquisition for Planning by Active Learning
Automatically acquiring control-knowledge for planning, as it is the case for Machine Learning in general, strongly depends on the training examples. In the case of planning, examp...
Raquel Fuentetaja, Daniel Borrajo
EMNLP
2007
13 years 10 months ago
Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...
Kenji Sagae, Jun-ichi Tsujii
PAA
2002
13 years 8 months ago
Bagging, Boosting and the Random Subspace Method for Linear Classifiers
: Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers. These techniques are designed for, and usually ...
Marina Skurichina, Robert P. W. Duin