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» Self-taught learning: transfer learning from unlabeled data
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CVPR
2010
IEEE
14 years 4 months ago
Optimizing One-Shot Recognition with Micro-Set Learning
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
SLSFS
2005
Springer
14 years 1 months ago
Constructing Visual Models with a Latent Space Approach
We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
EMNLP
2009
13 years 5 months ago
Graph Alignment for Semi-Supervised Semantic Role Labeling
Unknown lexical items present a major obstacle to the development of broadcoverage semantic role labeling systems. We address this problem with a semisupervised learning approach ...
Hagen Fürstenau, Mirella Lapata
AIED
2007
Springer
14 years 1 months ago
Accelerated Future Learning via Explicit Instruction of a Problem Solving Strategy
Explicit instruction in a problem-solving strategy accelerated learning not only in the domain where it was taught but also in a second domain where it was not taught. We present d...
Min Chi, Kurt VanLehn
IDEAL
2009
Springer
14 years 2 months ago
STORM - A Novel Information Fusion and Cluster Interpretation Technique
Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, usef...
Jan Feyereisl, Uwe Aickelin