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» Ensemble Learning Based on Multi-Task Class Labels
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ICASSP
2010
IEEE
14 years 11 months 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
113
Voted
SAC
2010
ACM
14 years 6 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane
149
Voted
PAMI
2012
13 years 2 months ago
CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
—We present a novel framework to generate and rank plausible hypotheses for the spatial extent of objects in images using bottom-up computational processes and mid-level selectio...
João Carreira, Cristian Sminchisescu
102
Voted
KDD
2006
ACM
191views Data Mining» more  KDD 2006»
16 years 23 hour ago
Beyond classification and ranking: constrained optimization of the ROI
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...
Lian Yan, Patrick Baldasare
99
Voted
GPEM
2008
128views more  GPEM 2008»
14 years 11 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood