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Sparse coding
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71	ITW 2007, Lake Tahoe, California, September 2 - 6, 2007 Nonlinear Sparse-Graph Codes for Lossy Compression of Discrete Nonredundant Sources Ankit Gupta Add to Reading List Source URL: www.princeton.edu Language: English - Date: 2008-11-03 19:55:31 Information Linear code Binary symmetric channel Block code Entropy Rate–distortion theory Generator matrix Low-density parity-check code Hamming Coding theory Information theory Discrete mathematics
72	Sparse Concept Coding for Visual Analysis Deng Cai Hujun Bao Xiaofei He The State Key Lab of CAD&CG, College of Computer Science, Zhejiang University 388 Yu Hang Tang Rd., Hangzhou, Zhejiang, China[removed] Add to Reading List Source URL: www.cad.zju.edu.cn Language: English - Date: 2014-05-22 00:27:13 Multivariate statistics Matrix theory Data analysis Singular value decomposition Non-negative matrix factorization Principal component analysis Nonlinear dimensionality reduction Latent semantic analysis Matrix Algebra Mathematics Linear algebra
73	doi:[removed]j.visres[removed] Add to Reading List Source URL: ahsu.psychol.ucl.ac.uk Language: English - Date: 2012-01-09 14:24:44 Neuroscience Visual system Cerebrum Neural coding Neural networks Visual cortex Orientation column Sparse coding Ocular dominance column Nervous system Biology Anatomy
74	Online Detection of Unusual Events in Videos via Dynamic Sparse Coding Bin Zhao School of Computer Science Carnegie Mellon University Li Fei-Fei Add to Reading List Source URL: vision.stanford.edu Language: English - Date: 2013-09-22 18:20:32 Assistive technology Closed-circuit television Crime prevention Security engineering Surveillance Security National security Public safety
75	Unsupervised Feature Learning by Deep Sparse Coding arXiv:1312.5783v1 [cs.LG] 20 Dec[removed]Yunlong He∗ Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-12-22 20:35:04 Cybernetics Learning Machine learning Sparse coding Matching pursuit Applied mathematics Artificial intelligence Caltech 101 Statistics Multivariate statistics Signal processing
76	Learning Invariant Feature Hierarchies Yann LeCun Courant Institute, New York University Abstract. Fast visual recognition in the mammalian cortex seems to be a hierarchical process by which the representation of the vis Add to Reading List Source URL: yann.lecun.com Language: English - Date: 2012-10-12 04:14:26 Learning Yann LeCun Unsupervised learning Neural network Supervised learning Pattern recognition Neocognitron Sparse coding Machine learning Artificial intelligence Science
77	LNCS[removed]Fast Approximations to Structured Sparse Coding and Applications to Object Classification Add to Reading List Source URL: yann.lecun.com Language: English - Date: 2012-10-12 04:15:00 Multivariate statistics Matching pursuit Signal processing Vector space Sparse matrix Matrix Vector quantization Trie Principal component analysis Algebra Mathematics Statistics
78	Response to Quian Quiroga et al. (2005) There are two competing theories regarding how the brain codes, represents, and integrates Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2013-02-17 12:24:49 Biology Nervous system Sparse coding Brain Neural networks Memory Neuron Mind Anatomy Neural coding
79	Opinion Sparse but not ‘Grandmother-cell’ coding in the medial temporal lobe R. Quian Quiroga1,2,3, G. Kreiman4,5, C. Koch2 and I. Fried3,6 1 Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2013-02-05 14:42:37 Cerebrum Neuroanatomy Limbic system Neural networks Nervous system Hippocampus Visual cortex Cerebral cortex Biological neural network Anatomy Biology Cognitive science
80	Nested Sparse Quantization for Efficient Feature Coding Xavier Boix1? , Gemma Roig1? , and Luc Van Gool1,2 1 ?? Add to Reading List Source URL: www.vision.ee.ethz.ch Language: English - Date: 2012-08-03 03:08:51 Vector quantization Quantum field theory Quantum mechanics Quantization Vector space Matrix Algebra Physics Mathematics

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