User contributions for J34liang
Jump to navigation
Jump to search
10 August 2013
- 12:3912:39, 10 August 2013 diff hist 0 N File:GarciaF14.jpg No edit summary current
- 11:5411:54, 10 August 2013 diff hist 0 N File:GarciaF13.jpg No edit summary current
- 11:5411:54, 10 August 2013 diff hist +570 rOBPCA: A New Approach to Robust Principal Component Analysis →Examples
- 11:4711:47, 10 August 2013 diff hist 0 N File:GarciaF12.jpg No edit summary current
9 August 2013
- 16:1716:17, 9 August 2013 diff hist +1,439 rOBPCA: A New Approach to Robust Principal Component Analysis →Diagnostic
- 16:1516:15, 9 August 2013 diff hist 0 N File:GarciaF11.jpg No edit summary current
- 15:3515:35, 9 August 2013 diff hist +296 rOBPCA: A New Approach to Robust Principal Component Analysis →Detailed ROBPCA algorithm
- 15:0915:09, 9 August 2013 diff hist −8 rOBPCA: A New Approach to Robust Principal Component Analysis →Detailed ROBPCA algorithm
- 15:0715:07, 9 August 2013 diff hist +1 rOBPCA: A New Approach to Robust Principal Component Analysis →Detailed ROBPCA algorithm
- 15:0615:06, 9 August 2013 diff hist +11 rOBPCA: A New Approach to Robust Principal Component Analysis →Detailed ROBPCA algorithm
- 15:0515:05, 9 August 2013 diff hist +8,296 N rOBPCA: A New Approach to Robust Principal Component Analysis Created page with "=Introduction= Principal component analysis (PCA) is a useful tool in statistical learning, which tries to preserve the variability by a small number of principal components. In..."
24 July 2013
- 12:3112:31, 24 July 2013 diff hist 0 parametric Local Metric Learning for Nearest Neighbor Classification →Learning the Weights
- 12:3112:31, 24 July 2013 diff hist 0 parametric Local Metric Learning for Nearest Neighbor Classification →Learning the Weights
- 12:2912:29, 24 July 2013 diff hist −2 parametric Local Metric Learning for Nearest Neighbor Classification →Learning the Weights
- 12:2712:27, 24 July 2013 diff hist +855 parametric Local Metric Learning for Nearest Neighbor Classification →Learning the Weights
20 July 2013
- 22:4322:43, 20 July 2013 diff hist +585 kernel Spectral Clustering for Community Detection in Complex Networks →Model Selection Criterion
- 22:3222:32, 20 July 2013 diff hist +1,143 kernel Spectral Clustering for Community Detection in Complex Networks →Selecting a Representative Subgraph
18 July 2013
- 16:0716:07, 18 July 2013 diff hist 0 maximum likelihood estimation of intrinsic dimension →Asymptotic behavior of the estimator
- 16:0616:06, 18 July 2013 diff hist 0 maximum likelihood estimation of intrinsic dimension →Asymptotic behavior of the estimator
14 July 2013
- 20:4720:47, 14 July 2013 diff hist +30 maximum likelihood estimation of intrinsic dimension →MLE of intrinsic dimension
- 20:4320:43, 14 July 2013 diff hist +4 maximum likelihood estimation of intrinsic dimension →Introduction
- 20:3920:39, 14 July 2013 diff hist −2 maximum likelihood estimation of intrinsic dimension →References
- 20:3920:39, 14 July 2013 diff hist +31 hamming Distance Metric Learning →Conclusion
- 20:3820:38, 14 July 2013 diff hist +1,010 hamming Distance Metric Learning →Conclusion
- 20:3820:38, 14 July 2013 diff hist 0 N File:GarciaF5.jpg No edit summary current
- 20:3720:37, 14 July 2013 diff hist 0 N File:GarciaF4.jpg No edit summary current
13 July 2013
- 23:1823:18, 13 July 2013 diff hist −2 maximum likelihood estimation of intrinsic dimension →Geometric methods
- 23:1523:15, 13 July 2013 diff hist −3 maximum likelihood estimation of intrinsic dimension →MLE of intrinsic dimension
- 23:1523:15, 13 July 2013 diff hist +31 maximum likelihood estimation of intrinsic dimension →Discussion
- 23:1523:15, 13 July 2013 diff hist −3 maximum likelihood estimation of intrinsic dimension →MLE of intrinsic dimension
- 23:1123:11, 13 July 2013 diff hist −11 maximum likelihood estimation of intrinsic dimension →MLE of intrinsic dimension
- 23:0723:07, 13 July 2013 diff hist −9 maximum likelihood estimation of intrinsic dimension →Geometric methods
- 23:0723:07, 13 July 2013 diff hist 0 maximum likelihood estimation of intrinsic dimension →Introduction
- 23:0223:02, 13 July 2013 diff hist 0 maximum likelihood estimation of intrinsic dimension →Experiments and comparison
- 23:0123:01, 13 July 2013 diff hist −3 maximum likelihood estimation of intrinsic dimension →Experiments and comparison
- 22:5922:59, 13 July 2013 diff hist 0 File:GarciaF1.jpg uploaded a new version of "File:GarciaF1.jpg": F1 current
- 22:5622:56, 13 July 2013 diff hist +14,522 maximum likelihood estimation of intrinsic dimension No edit summary
9 July 2013
- 22:0122:01, 9 July 2013 diff hist 0 N File:GarciaF3.jpg No edit summary current
- 22:0122:01, 9 July 2013 diff hist 0 N File:GarciaF2.jpg No edit summary current
- 22:0122:01, 9 July 2013 diff hist 0 N File:GarciaF1.jpg No edit summary
8 July 2013
- 18:3318:33, 8 July 2013 diff hist +1,856 s13Stat946proposal →Project 1 : How to Build a Bird House
7 July 2013
- 16:0916:09, 7 July 2013 diff hist +740 positive Semidefinite Metric Learning Using Boosting-like Algorithms →3. Optimization strategies
- 15:4015:40, 7 July 2013 diff hist +68 positive Semidefinite Metric Learning Using Boosting-like Algorithms →1. Mathematical model of the problem
- 14:5814:58, 7 July 2013 diff hist +595 inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method →Selecting Hyper-parameter
3 July 2013
- 17:2217:22, 3 July 2013 diff hist −1,195 maximum likelihood estimation of intrinsic dimension Blanked the page
- 17:2117:21, 3 July 2013 diff hist +1,195 N maximum likelihood estimation of intrinsic dimension Created page with "==Introduction== In dimensionality reduction (or manifold-learning) , the foundation of all methods is the belief that the observed data <math>\left\{ \mathbf{x}_{j} \right\}</ma..."
2 July 2013
- 13:4913:49, 2 July 2013 diff hist +242 stat946s13 →Set B
- 13:4713:47, 2 July 2013 diff hist +249 stat946s13 →Set A
- 13:4513:45, 2 July 2013 diff hist −13 stat946s13 →Sing up for paper presentation
- 13:4413:44, 2 July 2013 diff hist +7 stat946s13 →Sing up for paper presentation