搜索资源列表
Improved_Nystrom_Method.zip
- 流行学习，改进Nystrom降维方法，很好用，欢迎下载,Improved Nystrom Kernel Low-rank Approximation
SSC_test
- 稀疏表示 凸优化 低秩表示 用于聚类分析 -sparse representing, convex optimization low rank representing
low-rank-matrix-recovery
- 他能把前后景分开，把前景去除掉，形成稳定的背景图-He can separate foreground and background, the foreground removed to form a stable background
RASL_Code_CPP
- 鲁棒人脸识别的低秩表示,用来解决批量的人脸对齐问题。-Learning Low-Rank Representations with Classwise Block-Diagonal Structure for Robust Face Recognition
code of transfer learning code
- 基于低秩和稀疏表达的迁移子空间学习算法的代码(A migration subspace learning algorithm based on low rank and sparse representation)
程序
- 以稀疏子空间聚类以及低秩子空间聚类等基本谱聚类算法为基础，通过 运用核映射算法，融合与数据本身结构相关的局部切线空间函数以及主成分分析 算法建立了可以应对独立子空间聚类、非独立子空间聚类、非线性聚类、混合多 流体聚类问题以及多种含有大数据量的实际问题，包括处理运动分割、人脸识别、 工件识别等情况中的多种类型数据分类的聚类算法，并且引入 Map-Reduce 并行处 理方法优化了算法的计算效率(Based on the basic spectral clustering algorith
NLR_codes
- 压缩感知经典重建算法，非局部低秩算法，实现低秩正则约束，优化压缩图片质量。(Compressive Sensing via Nonlocal Low-Rank Regularization)
mo19beck_mfiles_v1.1
- 求解矩阵分解的算法，尤其是对于低秩优化和稀疏优化问题，该算法的效果很好。(The algorithm to solve the matrix decomposition, especially for low rank optimization and sparse optimization problems, the algorithm works well.)
VBLRMat
- 矩阵填充，低秩矩阵恢复，鲁棒PCA，低秩矩阵分解，跟大牛学习(Matrix Completion and Low rank matrix restoration)
RASL_Code
- 低秩矩阵恢复对齐， 论文 Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images(Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images)
chen2014
- LWI-SVD: Low-rank, Windowed, Incremental Singular Value Decompositions on Time-Evolving Data Sets
XZX
- 全局低秩显著性检测算法首先根据自然图像前景目标和背景亮度、颜色的差异性重构出图像前景显著目标；然后利用低秩分解对图像中的非显著性区域进行抑制。(The global low-rank saliency detection algorithm first reconstructs the image foreground salient targets based on the difference between the natural image foreground target and t
LRR
- LRR(低秩表示)假设一个数据矩阵严格的分布在一些独立的子空间。(LRR (Low Rank Representation) assumes that a data matrix is strictly distributed in some independent subspaces.)