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» Learning for Optical Flow Using Stochastic Optimization
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ICPR
2000
IEEE
14 years 1 months ago
Eigenfiltering for Flexible Eigentracking (EFE)
Traditional techniques for tracking non-rigid objects such as optical flow, correlation, active contours or color, can not deal with situations where image changes are not due to ...
Fernando De la Torre, Javier Melenchón, Jor...
FOCI
2007
IEEE
14 years 4 months ago
Almost All Learning Machines are Singular
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...
Sumio Watanabe
ICML
2010
IEEE
13 years 11 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
TVLSI
2008
176views more  TVLSI 2008»
13 years 10 months ago
A Fuzzy Optimization Approach for Variation Aware Power Minimization During Gate Sizing
Abstract--Technology scaling in the nanometer era has increased the transistor's susceptibility to process variations. The effects of such variations are having a huge impact ...
Venkataraman Mahalingam, N. Ranganathan, J. E. Har...
JMLR
2010
165views more  JMLR 2010»
13 years 4 months ago
Learning with Blocks: Composite Likelihood and Contrastive Divergence
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...