User contributions for Myakhave

14 August 2009

• 17:4917:49, 14 August 2009 diff hist +20‎ convex and Semi Nonnegative Matrix Factorization ‎ →‎SVD, Convex-NMF and Semi-NMF Comparison
• 17:4217:42, 14 August 2009 diff hist +35‎ convex and Semi Nonnegative Matrix Factorization ‎ →‎SVD, Convex-NMF and Semi-NMF Comparison
• 17:4017:40, 14 August 2009 diff hist −2‎ convex and Semi Nonnegative Matrix Factorization ‎ →‎SVD, Convex-NMF and Semi-NMF Comparison
• 17:4017:40, 14 August 2009 diff hist +144‎ convex and Semi Nonnegative Matrix Factorization ‎ →‎SVD, Convex-NMF and Semi-NMF comparison
• 17:2717:27, 14 August 2009 diff hist +541‎ convex and Semi Nonnegative Matrix Factorization ‎ →‎Convex NMF

13 August 2009

• 20:0920:09, 13 August 2009 diff hist +92‎ maximum-Margin Matrix Factorization ‎ →‎A short discussion on Loss Function for classification
• 19:3719:37, 13 August 2009 diff hist +3‎ maximum-Margin Matrix Factorization ‎ →‎Hinge Loss Function
• 19:3219:32, 13 August 2009 diff hist +12‎ maximum-Margin Matrix Factorization ‎ →‎Limitation
• 18:2318:23, 13 August 2009 diff hist +302‎ maximum-Margin Matrix Factorization ‎ →‎Experiments

28 July 2009

• 20:1620:16, 28 July 2009 diff hist −154‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 20:1020:10, 28 July 2009 diff hist +410‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:5219:52, 28 July 2009 diff hist −16‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:4919:49, 28 July 2009 diff hist −381‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:4319:43, 28 July 2009 diff hist +11‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:4319:43, 28 July 2009 diff hist −9‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:4219:42, 28 July 2009 diff hist −4‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:4119:41, 28 July 2009 diff hist −2‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 19:4019:40, 28 July 2009 diff hist +577‎ relevant Component Analysis ‎ →‎First paper: Shental et al., 2002 N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. European Conference on Computer Vision (ECCV), 2002, pp. 776-790.
• 16:5716:57, 28 July 2009 diff hist +211‎ visualizing Data using t-SNE ‎ →‎Compensation for Mismatched Dimensionality by Mismatched Tails
• 16:4016:40, 28 July 2009 diff hist +134‎ visualizing Data using t-SNE ‎ →‎The Crowding Problem
• 16:3416:34, 28 July 2009 diff hist +2‎ visualizing Data using t-SNE ‎ →‎The Crowding Problem
• 16:3116:31, 28 July 2009 diff hist +2‎ visualizing Data using t-SNE ‎ →‎The Crowding Problem
• 16:3116:31, 28 July 2009 diff hist +2‎ visualizing Data using t-SNE ‎ →‎The Crowding Problem
• 16:3016:30, 28 July 2009 diff hist +250‎ visualizing Data using t-SNE ‎ →‎The Crowding Problem
• 16:1716:17, 28 July 2009 diff hist +135‎ visualizing Data using t-SNE ‎ →‎The Crowding Problem

10 July 2009

• 19:2619:26, 10 July 2009 diff hist +12‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Modeling Human Word Association Data
• 19:2119:21, 10 July 2009 diff hist +179‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Modeling Human Word Association Data
• 19:1519:15, 10 July 2009 diff hist +386‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Modeling Human Word Association Data
• 18:4818:48, 10 July 2009 diff hist 0‎ independent Component Analysis: algorithms and applications ‎ →‎Finding hidden factors in financial data
• 18:4718:47, 10 July 2009 diff hist +231‎ independent Component Analysis: algorithms and applications ‎ →‎Finding hidden factors in financial data
• 18:4418:44, 10 July 2009 diff hist +679‎ independent Component Analysis: algorithms and applications ‎ →‎Applications
• 18:2718:27, 10 July 2009 diff hist +1‎ independent Component Analysis: algorithms and applications ‎ →‎Why Gaussian variables are forbidden
• 18:2118:21, 10 July 2009 diff hist −169‎ independent Component Analysis: algorithms and applications ‎ →‎Independence versus uncorrelatedness
• 18:2018:20, 10 July 2009 diff hist +313‎ independent Component Analysis: algorithms and applications ‎ →‎Independence versus uncorrelatedness
• 18:1618:16, 10 July 2009 diff hist +398‎ independent Component Analysis: algorithms and applications ‎ →‎Independence versus uncorrelatedness
• 18:0618:06, 10 July 2009 diff hist +246‎ independent Component Analysis: algorithms and applications ‎ →‎Why Gaussian variables are forbidden
• 10:4410:44, 10 July 2009 diff hist +4‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Stochastic Neighbour Embedding
• 10:3910:39, 10 July 2009 diff hist +20‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Stochastic Neighbour Embedding
• 10:3810:38, 10 July 2009 diff hist +592‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Stochastic Neighbour Embedding
• 10:1310:13, 10 July 2009 diff hist +1‎ visualizing Similarity Data with a Mixture of Maps ‎ →‎Introduction
• 09:5909:59, 10 July 2009 diff hist +147‎ nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization ‎ →‎Experimental Results
• 09:5609:56, 10 July 2009 diff hist +74‎ graph Laplacian Regularization for Larg-Scale Semidefinite Programming ‎ →‎Results
• 09:5509:55, 10 July 2009 diff hist 0‎ graph Laplacian Regularization for Larg-Scale Semidefinite Programming ‎ →‎Results
• 09:5309:53, 10 July 2009 diff hist +37‎ graph Laplacian Regularization for Larg-Scale Semidefinite Programming ‎ →‎Results

8 July 2009

• 22:2522:25, 8 July 2009 diff hist +165‎ graph Laplacian Regularization for Larg-Scale Semidefinite Programming ‎ →‎Introduction
• 22:2222:22, 8 July 2009 diff hist +14‎ nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization ‎ →‎References
• 22:2122:21, 8 July 2009 diff hist 0‎ nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization ‎ →‎Introduction
• 22:2022:20, 8 July 2009 diff hist +16‎ nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization ‎ →‎Experimental Results
• 22:2022:20, 8 July 2009 diff hist +260‎ nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization ‎ →‎Introduction
• 22:1922:19, 8 July 2009 diff hist +12‎ graph Laplacian Regularization for Larg-Scale Semidefinite Programming ‎ →‎Introduction