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» The Localization Hypothesis and Machines
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CIARP
2008
Springer
13 years 12 months ago
Learning and Forgetting with Local Information of New Objects
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Fernando Vázquez, José Salvador S&aa...
EDM
2010
140views Data Mining» more  EDM 2010»
13 years 11 months ago
Assessing Reviewer's Performance Based on Mining Problem Localization in Peer-Review Data
Current peer-review software lacks intelligence for responding to students' reviewing performance. As an example of an additional intelligent assessment component to such soft...
Wenting Xiong, Diane J. Litman, Christian D. Schun...
ICMLA
2008
13 years 11 months ago
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins
In this paper, we introduce two new formulations for multi-class multi-kernel relevance vector machines (mRVMs) that explicitly lead to sparse solutions, both in samples and in nu...
Theodoros Damoulas, Yiming Ying, Mark A. Girolami,...
ECTEL
2007
Springer
14 years 4 months ago
The Development of TE-Cap: An Assistance Environment for Online Tutors
Abstract. Our research is based on the hypothesis that the most important problem that has to be solved, so as to help tutors, is the gap between required competencies of distance ...
Élise Garrot, Sébastien George, Patr...
ICDM
2006
IEEE
182views Data Mining» more  ICDM 2006»
14 years 4 months ago
Active Learning to Maximize Area Under the ROC Curve
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
Matt Culver, Kun Deng, Stephen D. Scott