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» Learning a Classification Model for Segmentation
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121
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ECML
2006
Springer
15 years 6 months ago
Cost-Sensitive Learning of SVM for Ranking
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
Jun Xu, Yunbo Cao, Hang Li, Yalou Huang
155
Voted
PAMI
2012
13 years 5 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
146
Voted
WEBI
2010
Springer
15 years 12 days ago
Learning in Presence of Ontology Mapping Errors
The widespread use of ontologies to associate semantics with data has resulted in a growing interest in the problem of learning predictive models from data sources that use differe...
Neeraj Koul, Vasant Honavar
ESANN
2008
15 years 4 months ago
Interpretable ensembles of local models for safety-related applications
Abstract. This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach...
Sebastian Nusser, Clemens Otte, Werner Hauptmann
129
Voted
CVPR
2010
IEEE
15 years 11 months ago
Beyond Active Noun Tagging: Modeling Contextual Interactions for Multi-Class Active Learning
We present an active learning framework to simultaneously learn appearance and contextual models for scene understanding tasks (multi-class classification). Existing multi-class a...
Behjat Siddiquie, Abhinav Gupta