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» Learning Classifiers from Semantically Heterogeneous Data
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ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
EACL
2003
ACL Anthology
13 years 10 months ago
Learning to Identify Fragmented Words in Spoken Discourse
Disfluent speech adds to the difficulty of processing spoken language utterances. In this paper we concentrate on identifying one disfluency phenomenon: fragmented words. Our d...
Piroska Lendvai
TITB
2002
98views more  TITB 2002»
13 years 8 months ago
OILing the way to machine understandable bioinformatics resources
The complex questions and analyses posed by biologists, as well as the diverse data resources they develop, require the fusion of evidence from different, independently developed ...
Robert Stevens, Carole A. Goble, Ian Horrocks, Sea...
MIR
2010
ACM
167views Multimedia» more  MIR 2010»
14 years 3 months ago
Improving automatic music classification performance by extracting features from different types of data
This paper discusses two sets of automatic musical genre classification experiments. Promising research directions are then proposed based on the results of these experiments. The...
Cory McKay, Ichiro Fujinaga
SYNTHESE
2008
55views more  SYNTHESE 2008»
13 years 8 months ago
The semantics/pragmatics interface from an experimental perspective: the case of scalar implicature
In this paper I discuss some of the criteria that are widely used in the linguistic and philosophical literature to classify an aspect of meaning as either semantic or pragmatic. W...
Napoleon Katsos