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» Learning from Ambiguously Labeled Examples
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ICML
2008
IEEE
14 years 11 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin

Publication
922views
15 years 5 months ago
Multi-Class Active Learning for Image Classification
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
Ajay J. Joshi, Fatih Porikli, Nikolaos Papanikolop...
ICML
2009
IEEE
14 years 11 months ago
Uncertainty sampling and transductive experimental design for active dual supervision
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...
GFKL
2007
Springer
148views Data Mining» more  GFKL 2007»
14 years 5 months ago
Information Integration of Partially Labeled Data
Abstract. A central task when integrating data from different sources is to detect identical items. For example, price comparison websites have to identify offers for identical p...
Steffen Rendle, Lars Schmidt-Thieme
LREC
2010
191views Education» more  LREC 2010»
14 years 11 days ago
Spatial Role Labeling: Task Definition and Annotation Scheme
One of the essential functions of natural language is to talk about spatial relationships between objects. Linguistic constructs can express highly complex, relational structures ...
Parisa KordJamshidi, Martijn van Otterlo, Marie-Fr...