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ESANN
2008
15 years 1 months ago
Learning Data Representations with Sparse Coding Neural Gas
Abstract. We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the "sparse coding neural gas" algori...
Kai Labusch, Erhardt Barth, Thomas Martinetz
CONNECTION
2006
117views more  CONNECTION 2006»
14 years 12 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, ...
IJON
2007
117views more  IJON 2007»
14 years 11 months ago
Learning sensory representations with intrinsic plasticity
Intrinsic plasticity (IP) refers to a neuron’s ability to regulate its firing activity by adapting its intrinsic excitability. Previously, we showed that model neurons combinin...
Nicholas Butko, Jochen Triesch
ICIP
2004
IEEE
16 years 1 months ago
Learning structured dictionaries for image representation
The dictionary approach to signal and image processing has been massively investigated in the last two decades, proving very attractive for a wide range of applications. The effec...
Gianluca Monaci, Pierre Vandergheynst
ECAI
2008
Springer
15 years 1 months ago
Learning Functional Object-Categories from a Relational Spatio-Temporal Representation
Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...