Structured Sparse Priors for Image Classification
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Trac D. Tran | Vishal Monga | Minh Dao | Yuanming Suo | Umamahesh Srinivas | T. Tran | V. Monga | U. Srinivas | Yuanming Suo | Minh Dao
[1] M. Turk,et al. Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.
[2] E. George,et al. Journal of the American Statistical Association is currently published by American Statistical Association. , 2007 .
[3] Hugh Chipman,et al. Bayesian variable selection with related predictors , 1995, bayes-an/9510001.
[4] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[5] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[6] David J. Field,et al. Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.
[7] David J. Kriegman,et al. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.
[8] Aleix M. Martinez,et al. The AR face database , 1998 .
[9] A. Martínez,et al. The AR face databasae , 1998 .
[10] J. Anthony Gualtieri,et al. Support vector machines for hyperspectral remote sensing classification , 1999, Other Conferences.
[11] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[12] David J. Kriegman,et al. From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[13] George Eastman House,et al. Sparse Bayesian Learning and the Relevance Vector Machine , 2001 .
[14] Michael W. Marcellin,et al. JPEG2000 - image compression fundamentals, standards and practice , 2002, The Kluwer International Series in Engineering and Computer Science.
[15] Azriel Rosenfeld,et al. Face recognition: A literature survey , 2003, CSUR.
[16] David J. Kriegman,et al. Clustering appearances of objects under varying illumination conditions , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[17] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[18] J. S. Rao,et al. Spike and slab variable selection: Frequentist and Bayesian strategies , 2005, math/0505633.
[19] H. Zou,et al. Regularization and variable selection via the elastic net , 2005 .
[20] Richard G. Baraniuk,et al. Distributed Compressed Sensing Dror , 2005 .
[21] A. Bruckstein,et al. K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .
[22] D. Donoho. For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution , 2006 .
[23] Emmanuel J. Candès,et al. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.
[24] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[25] M. Elad,et al. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.
[26] Jitendra Malik,et al. SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[27] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .
[28] Andrew Zisserman,et al. A Visual Vocabulary for Flower Classification , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[29] D. Donoho,et al. Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.
[30] Lawrence Carin,et al. Bayesian Compressive Sensing , 2008, IEEE Transactions on Signal Processing.
[31] Junzhou Huang,et al. Simultaneous image transformation and sparse representation recovery , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[32] M. West,et al. High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics , 2008, Journal of the American Statistical Association.
[33] Yongsheng Gao,et al. Face recognition across pose: A review , 2009, Pattern Recognit..
[34] Lawrence Carin,et al. Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing , 2009, IEEE Transactions on Signal Processing.
[35] Michael Elad,et al. From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images , 2009, SIAM Rev..
[36] Babak Hassibi,et al. On the Reconstruction of Block-Sparse Signals With an Optimal Number of Measurements , 2008, IEEE Transactions on Signal Processing.
[37] Yonina C. Eldar,et al. Robust Recovery of Signals From a Structured Union of Subspaces , 2008, IEEE Transactions on Information Theory.
[38] Mike E. Davies,et al. Sampling Theorems for Signals From the Union of Finite-Dimensional Linear Subspaces , 2009, IEEE Transactions on Information Theory.
[39] Volkan Cevher,et al. Learning with Compressible Priors , 2009, NIPS.
[40] Sebastian Nowozin,et al. On feature combination for multiclass object classification , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[41] A. Madabhushi,et al. Histopathological Image Analysis: A Review , 2009, IEEE Reviews in Biomedical Engineering.
[42] Allen Y. Yang,et al. Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[43] Rabab Kreidieh Ward,et al. Classification via group sparsity promoting regularization , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[44] Garrison W. Cottrell,et al. Robust classification of objects, faces, and flowers using natural image statistics , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[45] Allen Y. Yang,et al. Fast ℓ1-minimization algorithms and an application in robust face recognition: A review , 2010, 2010 IEEE International Conference on Image Processing.
[46] Michael Elad,et al. Dictionaries for Sparse Representation Modeling , 2010, Proceedings of the IEEE.
[47] Rabab Kreidieh Ward,et al. Improved Group Sparse Classifier , 2010, Pattern Recognit. Lett..
[48] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[49] Volkan Cevher,et al. Sparse Signal Recovery and Acquisition with Graphical Models , 2010, IEEE Signal Processing Magazine.
[50] Shuicheng Yan,et al. Visual classification with multi-task joint sparse representation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[51] Aggelos K. Katsaggelos,et al. Bayesian Compressive Sensing Using Laplace Priors , 2010, IEEE Transactions on Image Processing.
[52] Volkan Cevher,et al. Model-Based Compressive Sensing , 2008, IEEE Transactions on Information Theory.
[53] Yang Yu,et al. Group sparsity based classification for cervigram segmentation , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[54] Anil K. Jain,et al. Handbook of Face Recognition, 2nd Edition , 2011 .
[55] Hugues Talbot,et al. A Memory Gradient algorithm for ℓ2 — ℓ0 regularization with applications to image restoration , 2011, 2011 18th IEEE International Conference on Image Processing.
[56] Yonina C. Eldar,et al. Structured Compressed Sensing: From Theory to Applications , 2011, IEEE Transactions on Signal Processing.
[57] David Zhang,et al. Fisher Discrimination Dictionary Learning for sparse representation , 2011, 2011 International Conference on Computer Vision.
[58] Jian Yang,et al. Robust sparse coding for face recognition , 2011, CVPR 2011.
[59] T. Yen. A majorization–minimization approach to variable selection using spike and slab priors , 2010, 1005.0891.
[60] Rama Chellappa,et al. Secure and Robust Iris Recognition Using Random Projections and Sparse Representations , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[61] Miguel Lázaro-Gredilla,et al. Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning , 2011, NIPS.
[62] Yonina C. Eldar,et al. C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework , 2010, IEEE Transactions on Signal Processing.
[63] Andrew Zisserman,et al. BiCoS: A Bi-level co-segmentation method for image classification , 2011, 2011 International Conference on Computer Vision.
[64] Yoshua Bengio,et al. Large-Scale Feature Learning With Spike-and-Slab Sparse Coding , 2012, ICML.
[65] Julien Mairal,et al. Optimization with Sparsity-Inducing Penalties , 2011, Found. Trends Mach. Learn..
[66] Hossein Mobahi,et al. Toward a Practical Face Recognition System: Robust Alignment and Illumination by Sparse Representation , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[67] Katherine A. Heller,et al. Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning , 2011, ICML.
[68] Thomas S. Huang,et al. Joint-Structured-Sparsity-Based Classification for Multiple-Measurement Transient Acoustic Signals , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[69] Shuicheng Yan,et al. Visual Classification With Multitask Joint Sparse Representation , 2012, IEEE Transactions on Image Processing.
[70] Hugues Talbot,et al. A Majorize-Minimize Subspace Approach for ℓ2-ℓ0 Image Regularization , 2011, SIAM J. Imaging Sci..
[71] Michael W. Marcellin,et al. JPEG2000 - image compression fundamentals, standards and practice , 2013, The Kluwer international series in engineering and computer science.
[72] Trac D. Tran,et al. Structured sparse priors for image classification , 2013, ICIP.
[73] Trac D. Tran,et al. Hierarchical sparse modeling using Spike and Slab priors , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.