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» Reinforcement Learning with Time
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135
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ICML
2009
IEEE
16 years 4 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
NIPS
2000
15 years 5 months ago
Temporally Dependent Plasticity: An Information Theoretic Account
The paradigm of Hebbian learning has recently received a novel interpretation with the discovery of synaptic plasticity that depends on the relative timing of pre and post synapti...
Gal Chechik, Naftali Tishby
CVPR
2008
IEEE
16 years 6 months ago
Fast image search for learned metrics
We introduce a method that enables scalable image search for learned metrics. Given pairwise similarity and dissimilarity constraints between some images, we learn a Mahalanobis d...
Prateek Jain, Brian Kulis, Kristen Grauman
130
Voted
ICML
2006
IEEE
16 years 4 months ago
Learning hierarchical task networks by observation
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Negin Nejati, Pat Langley, Tolga Könik
136
Voted
HIS
2009
15 years 1 months ago
Applying Concept Mapping on the Influent Learning in Virtual Classroom
The diversity of learning abilities between learners in the virtual classroom is wider than those in traditional classroom. It is difficult to prepare a suitable teaching material ...
Rong-Chung Chen, Shu-Chen Liu