By Neamat El Gayar, Friedhelm Schwenker, Cheng Suen
This e-book constitutes the refereed court cases of the sixth IAPR TC3 overseas Workshop on synthetic Neural Networks in development reputation, ANNPR 2014, held in Montreal, quality control, Canada, in October 2014. The 24 revised complete papers awarded have been rigorously reviewed and chosen from 37 submissions for inclusion during this quantity. They disguise a wide range of issues within the box of studying algorithms and architectures and discussing the newest learn, effects, and ideas in those areas.
Read or Download Artificial Neural Networks in Pattern Recognition: 6th IAPR TC 3 International Workshop, ANNPR 2014, Montreal, QC, Canada, October 6-8, 2014. Proceedings PDF
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Extra info for Artificial Neural Networks in Pattern Recognition: 6th IAPR TC 3 International Workshop, ANNPR 2014, Montreal, QC, Canada, October 6-8, 2014. Proceedings
M. : New training strategies for constructive neural networks with application to regression problems. Neural Netw. : Advances in neural information processing systems 2, pp. 598–605. : A penalty-function approach for pruning feedforward neural networks. Neural Comput. : A simple neural network pruning algorithm with application to ﬁlter synthesis. Neural Process. Lett. : Reduced-size neural networks through singular value decomposition and subset selection. : Optimizing the number of hidden nodes of a feedforward artiﬁcial neural network.
To evaluate our paradigm, we applied XLADA on English-French and English-Chinese bilingual corpora then we trained French and Chinese information extraction models. The experimental results show that XLADA can produce eﬀective models without manually-annotated training data. Keywords: Information extraction, named entity recognition, crosslingual domain adaptation, unsupervised active learning. 1 Introduction Named Entity Recognition (NER) is an information extraction task that identiﬁes the names of locations, persons, organizations and other named entities in text, which plays an important role in many Natural Language Processing (NLP) applications such as information retrieval and machine translation.
In: Advances in Neural Information Processing Systems 2, pp. 524–532. : Constructive algorithms for structure learning in feedforward neural networks for regression problems. : A resource-allocating network for function interpolation. Neural Comput. : A structure optimisation algorithm for feedforward neural network construction. Neurocomput. : Constructive algorithms for structure learning in feedforward neural networks for regression problems. : A new training and pruning algorithm based on node dependence and jacobian rank deﬁciency.