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127
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CVPR
2011
IEEE
14 years 11 months ago
Learning invariance through imitation
Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approac...
Graham Taylor, Ian Spiro, Rob Fergus, Christoph Br...
134
Voted
ECTEL
2007
Springer
15 years 9 months ago
Organizational Management of e-Learning in Universities - Significant Issues
Educational technology in higher education has not managed to match the ubiquity of technology in everyday life. Is this because higher education institutions are inherently resis...
Su White
124
Voted
ISCAS
2006
IEEE
144views Hardware» more  ISCAS 2006»
15 years 9 months ago
A VLSI spike-driven dynamic synapse which learns only when necessary
— We describe an analog VLSI circuit implementing spike-driven synaptic plasticity, embedded in a network of integrate-and-fire neurons. This biologically inspired synapse is hi...
S. Mitra, Stefano Fusi, Giacomo Indiveri
178
Voted
MICCAI
2005
Springer
15 years 9 months ago
Learning Best Features for Deformable Registration of MR Brains
Abstract. This paper presents a learning method to select best geometric features for deformable brain registration. Best geometric features are selected for each brain location, a...
Guorong Wu, Feihu Qi, Dinggang Shen
124
Voted
IJCAI
2007
15 years 5 months ago
Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD...
Ah-Hwee Tan