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ACL
1998
13 years 11 months ago
A Connectionist Architecture for Learning to Parse
We present a connectionist architecture and demonstrate that it can learn syntactic parsing from a corpus of parsed text. The architecture can represent syntactic constituents, an...
James Henderson, Peter Lane
TNN
2011
137views more  TNN 2011»
13 years 5 months ago
Learning Pattern Recognition Through Quasi-Synchronization of Phase Oscillators
—The idea that synchronized oscillations are important in cognitive tasks is receiving significant attention. In this view, single neurons are no longer elementary computational...
Ekaterina Vassilieva, Guillaume Pinto, J. Acacio d...
CORR
2011
Springer
222views Education» more  CORR 2011»
13 years 1 months ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn
CIBCB
2006
IEEE
14 years 4 months ago
Machine Learning in Basecalling Decoding Trace Peak Behaviour
— DNA sequence basecalling is commonly regarded as a solved problem, despite significant error rates being reflected in inaccuracies in databases and genome annotations. These er...
David Thornley, Stavros Petridis
CCR
2006
114views more  CCR 2006»
13 years 10 months ago
A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular m...
Nigel Williams, Sebastian Zander, Grenville J. Arm...