By Yupei Zhang

本文探讨了稀疏学习在不同领域的应用,包括基于稀疏编码的视觉特征提取、统计特征选择、聚类分析及结构化稀疏学习等。此外还介绍了流形学习的基本概念。

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Sparse Learning:

Sparsity Learning (foundation)

    (1) Emergence of simple-cell receptive field properties by learning a sparse code for natural images.

         "Appearing in Nature-1996".[PDF]

         Its detailed version is:

         Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1? 

         "Appear in Vision Research-1997".[PDF]

    (2) Regression and Selection via The Lasso. "Appearing in JRSS-1996".    [PDF]

    The noted study of sparsity for feature selection in statistics.

Sparsity Learning for Clustering

    (1) sparse subspace clustering: Algorithm, Theory and Applications. "Appearing in PAMI-2013".     [PDF]

    The collection of data from multiple classes or categories lies in a union of low-dimensional subspaces.

    (2) 

Group (Structured) Sparsity Learning

    (1) Learning with Structured Sparsity. "Appearing in ICML-2009 and JMLR-2011".[PDF]
         Algorithm, dubbed structOMP, was proposed for learning structured sparsity.
    (2)

Sparsity Learning for Classification


Manifold Learning:

i) 

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