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» Extracting Propositions from Trained Neural Networks
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EMNLP
2006
15 years 1 months ago
Loss Minimization in Parse Reranking
We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
Ivan Titov, James Henderson
IJISTA
2007
124views more  IJISTA 2007»
14 years 11 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
ICDAR
2009
IEEE
14 years 9 months ago
Low Cost Correction of OCR Errors Using Learning in a Multi-Engine Environment
We propose a low cost method for the correction of the output of OCR engines through the use of human labor. The method employs an error estimator neural network that learns to as...
Ahmad Abdulkader, Mathew R. Casey
ICASSP
2010
IEEE
15 years 1 hour ago
Classifying laughter and speech using audio-visual feature prediction
In this study, a system that discriminates laughter from speech by modelling the relationship between audio and visual features is presented. The underlying assumption is that thi...
Stavros Petridis, Ali Asghar, Maja Pantic
NCA
2007
IEEE
14 years 11 months ago
A data reduction approach for resolving the imbalanced data issue in functional genomics
Learning from imbalanced data occurs frequently in many machine learning applications. One positive example to thousands of negative instances is common in scientific applications...
Kihoon Yoon, Stephen Kwek