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» On Variations of Power Iteration
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ICMLA
2010
13 years 6 months ago
Ensembles of Neural Networks for Robust Reinforcement Learning
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Alexander Hans, Steffen Udluft
CVPR
2005
IEEE
14 years 10 months ago
Optimal Sub-Shape Models by Minimum Description Length
Active shape models are a powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowle...
Georg Langs, Philipp Peloschek, Horst Bischof
ICCAD
2004
IEEE
88views Hardware» more  ICCAD 2004»
14 years 5 months ago
Interconnect lifetime prediction under dynamic stress for reliability-aware design
Thermal effects are becoming a limiting factor in highperformance circuit design due to the strong temperaturedependence of leakage power, circuit performance, IC package cost and...
Zhijian Lu, Wei Huang, John Lach, Mircea R. Stan, ...
TCAD
2010
116views more  TCAD 2010»
13 years 3 months ago
MeshWorks: A Comprehensive Framework for Optimized Clock Mesh Network Synthesis
Clock mesh networks are well known for their variation tolerance. But their usage is limited to high-end designs due to the significantly high resource requirements compared to clo...
Anand Rajaram, David Z. Pan
ISBI
2011
IEEE
12 years 12 months ago
Principal components regression: Multivariate, gene-based tests in imaging genomics
In imaging genomics, there have been rapid advances in genome-wide, image-wide searches for genes that influence brain structure. Most efforts focus on univariate tests that treat...
Derrek P. Hibar, Jason L. Stein, Omid Kohannim, Ne...