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NAACL
2007
15 years 7 months ago
Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
We present a method for utilizing unannotated sentences to improve a semantic parser which maps natural language (NL) sentences into their formal meaning representations (MRs). Gi...
Rohit J. Kate, Raymond J. Mooney
ICRA
2007
IEEE
157views Robotics» more  ICRA 2007»
16 years 21 days ago
Learning to Select State Machines using Expert Advice on an Autonomous Robot
— Hierarchical state machines have proven to be a powerful tool for controlling autonomous robots due to their flexibility and modularity. For most real robot implementations, h...
Brenna Argall, Brett Browning, Manuela M. Veloso
ICANN
2010
Springer
15 years 7 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel
LREC
2010
213views Education» more  LREC 2010»
15 years 7 months ago
Active Learning and Crowd-Sourcing for Machine Translation
In recent years, corpus based approaches to machine translation have become predominant, with Statistical Machine Translation (SMT) being the most actively progressing area. Succe...
Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell
144
Voted
CEC
2007
IEEE
15 years 10 months ago
Support vector machines for computing action mappings in learning classifier systems
XCS with Computed Action, briefly XCSCA, is a recent extension of XCS to tackle problems involving a large number of discrete actions. In XCSCA the classifier action is computed wi...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi