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» Additive Preconditioning for Matrix Computations
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99
Voted
CVPR
2005
IEEE
16 years 7 days ago
Fisher+Kernel Criterion for Discriminant Analysis
We simultaneously approach two tasks of nonlinear discriminant analysis and kernel selection problem by proposing a unified criterion, Fisher+Kernel Criterion. In addition, an eff...
Shu Yang, Shuicheng Yan, Dong Xu, Xiaoou Tang, Cha...
CVPR
2007
IEEE
16 years 7 days ago
Element Rearrangement for Tensor-Based Subspace Learning
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
93
Voted
CVPR
2008
IEEE
16 years 6 days ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
78
Voted
ICML
2008
IEEE
15 years 11 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
85
Voted
ICCS
2009
Springer
15 years 4 months ago
A Note on Auto-tuning GEMM for GPUs
The development of high performance dense linear algebra (DLA) critically depends on highly optimized BLAS, and especially on the matrix multiplication routine (GEMM). This is espe...
Yinan Li, Jack Dongarra, Stanimire Tomov