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NIPS
2004
13 years 9 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
DEXA
2003
Springer
95views Database» more  DEXA 2003»
14 years 1 months ago
XML and Knowledge Technologies for Semantic-Based Indexing of Paper Documents
Effective daily processing of large amounts of paper documents in office environments requires the application of semantic-based indexing techniques during the transformation of pa...
Donato Malerba, Michelangelo Ceci, Margherita Bera...
TNN
1998
125views more  TNN 1998»
13 years 8 months ago
Symbolic connectionism in natural language disambiguation
Abstract—Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language an...
Samuel W. K. Chan, James Franklin
TASLP
2008
98views more  TASLP 2008»
13 years 8 months ago
An Integrative and Discriminative Technique for Spoken Utterance Classification
Abstract-- Traditional methods of spoken utterance classification (SUC) adopt two independently trained phases. In the first phase, an automatic speech recognition (ASR) module ret...
Sibel Yaman, Li Deng, Dong Yu, Ye-Yi Wang, Alex Ac...
CORR
2002
Springer
132views Education» more  CORR 2002»
13 years 8 months ago
Exploiting Synergy Between Ontologies and Recommender Systems
Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender sys...
Stuart E. Middleton, Harith Alani, David De Roure