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Description: 多种信号过完备字典学习算法的工具包，包含文献Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms中所有的算法。-Multiple signals over-complete dictionary learning algorithm toolkit, including literature Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms for all algorithms.
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Size: 13312 |
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Description: Locally-Linear Embedding (LLE)[9] was presented at approximately the same time as Isomap. It has several advantages over Isomap, including faster optimization when implemented to take advantage of sparse matrix algorithms, and better results with many problems. LLE also begins by finding a set of the nearest neighbors of each point. It then computes a set of weights for each point that best describe the point as a linear combination of its neighbors. Finally, it uses an eigenvector-based optimization technique to find the low-dimensional embedding of points, such that each point is still described with the same linear combination of its neighbors. LLE tends to handle non-uniform sample densities poorly because there is no fixed unit to prevent the weights from drifting as various regions differ in sample densities. LLE has no internal model.
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Size: 2048 |
Author: Karthikeyan |
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Description: 稀疏流形建模及其在人脸识别中的应用论文介绍稀疏理论 以及sparse LLE
-Sparse manifold modeling and its application to face recognition paper introduces the theory and sparse LLE sparse
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Size: 1511424 |
Author: John |
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