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» Learning Overcomplete Representations
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PR
2007
96views more  PR 2007»
13 years 8 months ago
Weighted and robust learning of subspace representations
A reliable system for visual learning and recognition should enable a selective treatment of individual parts of input data and should successfully deal with noise and occlusions....
Danijel Skocaj, Ales Leonardis, Horst Bischof
CVPR
2008
IEEE
14 years 10 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell
CE
2008
128views more  CE 2008»
13 years 8 months ago
Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments
Although most online learning environments are predominately text based, researchers have argued that representational support for the conceptual structure of a problem would addr...
Daniel D. Suthers, Ravi K. Vatrapu, Richard Medina...
JURIX
2007
13 years 10 months ago
A Modular Framework for Ontology-based Representation of Patent Information
Abstract. In this paper, we present a new ontology-based formalism for representing patent information. The framework defines concepts and relations for the major aspects of paten...
Mark Giereth, Steffen Koch, Yiannis Kompatsiaris, ...
CONNECTION
2006
117views more  CONNECTION 2006»
13 years 8 months ago
Bootstrap learning of foundational representations
To be autonomous, intelligent robots must learn the foundations of commonsense knowledge from their own sensorimotor experience in the world. We describe four recent research resu...
Benjamin Kuipers, Patrick Beeson, Joseph Modayil, ...