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» Exploiting multiple classifier types with active learning
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IJCAI
2001
13 years 8 months ago
Probabilistic Classification and Clustering in Relational Data
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Benjamin Taskar, Eran Segal, Daphne Koller
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 7 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
CVPR
2009
IEEE
15 years 1 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
CLEF
2010
Springer
13 years 7 months ago
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees
Abstract. In this paper, we present a multiple targets classification system for visual concepts detection and image annotation. Multiple targets classification (MTC) is a variant ...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
IJON
2010
148views more  IJON 2010»
13 years 4 months ago
Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
Several solutions have been proposed to exploit the availability of heterogeneous sources of biomolecular data for gene function prediction, but few attention has been dedicated t...
Matteo Re, Giorgio Valentini