311 search results - page 16 / 63 » Gradient Convergence in Gradient methods with Errors |
SIAMSC
2008
13 years 7 months ago
2008
Abstract. A new iterative algorithm for the solution of minimization problems in infinitedimensional Hilbert spaces which involve sparsity constraints in form of p-penalties is pro...
EOR
2000
13 years 7 months ago
2000
Training in the random neural network (RNN) is generally speci
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Real-time functional magnetic resonance imaging (rtfMRI) enables classification of brain activity during data collection thus making inference results accessible to both the subj...
JMLR
2010
13 years 2 months ago
2010
Contrastive Divergence (CD) is a popular method for estimating the parameters of Markov Random Fields (MRFs) by rapidly approximating an intractable term in the gradient of the lo...
JMLR
2008
13 years 7 months ago
2008
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...