User contributions for Vmaroufy
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12 July 2009
- 19:5819:58, 12 July 2009 diff hist −11 relevant Component Analysis →Kernelizing RCA
- 19:5719:57, 12 July 2009 diff hist +244 relevant Component Analysis →Kernelizing RCA
- 19:5119:51, 12 July 2009 diff hist +142 relevant Component Analysis →Kernelizing RCA
- 19:4719:47, 12 July 2009 diff hist +1 relevant Component Analysis →Kernelizing RCA
- 19:4719:47, 12 July 2009 diff hist +436 relevant Component Analysis →Kernelizing RCA
- 19:3619:36, 12 July 2009 diff hist +2 relevant Component Analysis →Kernelizing RCA
- 19:3619:36, 12 July 2009 diff hist +125 relevant Component Analysis →Kernel RCA
- 19:3119:31, 12 July 2009 diff hist −17 relevant Component Analysis →Kernelizing RCA
- 19:3019:30, 12 July 2009 diff hist +244 relevant Component Analysis →Kernel RCA
- 19:2419:24, 12 July 2009 diff hist +755 relevant Component Analysis →Suggestions/Critique
- 16:4416:44, 12 July 2009 diff hist +1 independent Component Analysis: algorithms and applications →Kernel ICA Bach and Jordan,(2002); Kernel Independent Component Analysis. Journal of Machine Learning Research, 3; 1-48
- 16:3616:36, 12 July 2009 diff hist −9 relevant Component Analysis →First paper: Shental et al., 2002 [1]
- 16:3516:35, 12 July 2009 diff hist +9 relevant Component Analysis →First paper: Shental et al., 2002 [1]
- 15:3515:35, 12 July 2009 diff hist +7 kernelized Sorting →Relaxation to a constrained eigenvalue problem
- 15:3415:34, 12 July 2009 diff hist +24 kernelized Sorting →Relaxation to a constrained eigenvalue problem
- 15:3215:32, 12 July 2009 diff hist +14 kernelized Sorting →Relaxation to a constrained eigenvalue problem
- 15:3115:31, 12 July 2009 diff hist −9 kernelized Sorting →Relaxation to a constrained eigenvalue problem
9 July 2009
- 11:5611:56, 9 July 2009 diff hist +2 paper 13 →Upper and Lower Bound for estimator of K
- 11:5511:55, 9 July 2009 diff hist +12 paper 13 →Upper and Lower Bound for estimator of K
- 11:4411:44, 9 July 2009 diff hist +12 paper 13 →Lower Bound for the number of Random Projections
- 11:4311:43, 9 July 2009 diff hist +14 paper 13 →Lower Bound for the number of Random Projections
- 11:3811:38, 9 July 2009 diff hist +4 paper 13 →Upper and Lower Bound for estimator of K
- 11:3811:38, 9 July 2009 diff hist +3 paper 13 →Upper and Lower Bound for estimator K
- 11:3411:34, 9 July 2009 diff hist +1 paper 13 →Introduction
- 11:3311:33, 9 July 2009 diff hist +1 paper 13 →Introduction
- 11:3211:32, 9 July 2009 diff hist +22 paper 13 →Introduction
- 11:2411:24, 9 July 2009 diff hist +65 paper 13 →Random mapping (Random Projection)
- 11:0911:09, 9 July 2009 diff hist +5 graph Laplacian Regularization for Larg-Scale Semidefinite Programming →Sensor localization
- 11:0711:07, 9 July 2009 diff hist +13 graph Laplacian Regularization for Larg-Scale Semidefinite Programming →Introduction
- 11:0211:02, 9 July 2009 diff hist +32 graph Laplacian Regularization for Larg-Scale Semidefinite Programming →Introduction
- 10:5710:57, 9 July 2009 diff hist +2 graph Laplacian Regularization for Larg-Scale Semidefinite Programming →Introduction
- 10:5610:56, 9 July 2009 diff hist 0 graph Laplacian Regularization for Larg-Scale Semidefinite Programming →Matrix factorization
- 10:4310:43, 9 July 2009 diff hist +1 convex and Semi Nonnegative Matrix Factorization →Kernel NMF
- 10:3910:39, 9 July 2009 diff hist +27 convex and Semi Nonnegative Matrix Factorization →Sparsity of Convex NMF
7 July 2009
- 12:0012:00, 7 July 2009 diff hist +46 independent Component Analysis: algorithms and applications →Kernel ICA Bach and Jordan,(2002); Kernel Independent Component Analysis
- 11:5811:58, 7 July 2009 diff hist +31 independent Component Analysis: algorithms and applications →A brief history of ICA
- 11:5611:56, 7 July 2009 diff hist +74 independent Component Analysis: algorithms and applications →Kernel ICA
- 11:5111:51, 7 July 2009 diff hist +409 independent Component Analysis: algorithms and applications →A brief history of ICA
- 09:3609:36, 7 July 2009 diff hist +25 independent Component Analysis: algorithms and applications →Principle 2: Maximizing Non-gaussanity
- 09:3509:35, 7 July 2009 diff hist +24 independent Component Analysis: algorithms and applications →Principle 2: Maximizing Non-gaussanity
5 July 2009
- 21:0821:08, 5 July 2009 diff hist 0 visualizing Similarity Data with a Mixture of Maps →Stochastic Neighbour Embedding
2 July 2009
- 16:0716:07, 2 July 2009 diff hist −6 stat946f10 →Application
- 16:0516:05, 2 July 2009 diff hist +7 stat946f10 →Algorithmic Modification
- 16:0216:02, 2 July 2009 diff hist −1 stat946f10 →Colored Maximum Variance Unfolding .Song, L. and colleagues; Proceedings of the 2007 Conference, 1385-1392.
- 16:0116:01, 2 July 2009 diff hist +1 stat946f10 →Colored Maximum Variance Unfolding .Song, L. and colleagues; Proceedings of the 2007 Conference, 1385-1392.
- 15:5015:50, 2 July 2009 diff hist +4 measuring Statistical Dependence with Hilbert-Schmidt Norm →Principle Components Analysis (PCA)
- 12:0012:00, 2 July 2009 diff hist 0 measuring Statistical Dependence with Hilbert-Schmidt Norm →Independence Test using HSIC
- 11:4411:44, 2 July 2009 diff hist +14 measuring Statistical Dependence with Hilbert-Schmidt Norm →The independence measure
- 11:4211:42, 2 July 2009 diff hist −61 measuring Statistical Dependence with Hilbert-Schmidt Norm →The independence measure
- 10:5510:55, 2 July 2009 diff hist +61 measuring Statistical Dependence with Hilbert-Schmidt Norm →The independence measure