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BDA
2007
14 years 11 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
JMLR
2010
163views more  JMLR 2010»
14 years 4 months ago
Active Sequential Learning with Tactile Feedback
We consider the problem of tactile discrimination, with the goal of estimating an underlying state parameter in a sequential setting. If the data is continuous and highdimensional...
Hannes Saal, Jo-Anne Ting, Sethu Vijayakumar
JODL
2007
126views more  JODL 2007»
14 years 9 months ago
Building rich, semantic descriptions of learning activities to facilitate reuse in digital libraries
Abstract This paper describes efforts to extend educational descriptions of learning objects to enable semantic search for suitable resources held within digital libraries and cybe...
Mark Gahegan, Ritesh Agrawal, Tawan Banchuen, Davi...
WWW
2009
ACM
15 years 10 months ago
Advertising keyword generation using active learning
This paper proposes an efficient relevance feedback based interactive model for keyword generation in sponsored search advertising. We formulate the ranking of relevant terms as a...
Hao Wu, Guang Qiu, Xiaofei He, Yuan Shi, Mingcheng...
ICCV
2007
IEEE
15 years 12 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...