Class-Specific Kernel Discriminant Analysis Revisited: Further Analysis and Extensions
暂无分享,去创建一个
[1] Jun Wang,et al. A 3D facial expression database for facial behavior research , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).
[2] Alexandros Iosifidis,et al. On the Optimal Class Representation in Linear Discriminant Analysis , 2013, IEEE Transactions on Neural Networks and Learning Systems.
[3] Alexandros Iosifidis,et al. Activity-Based Person Identification Using Fuzzy Representation and Discriminant Learning , 2012, IEEE Transactions on Information Forensics and Security.
[4] Alexander J. Smola,et al. Learning with kernels , 1998 .
[5] G. Stewart. Matrix Algorithms, Volume II: Eigensystems , 2001 .
[6] Shaoning Pang,et al. Incremental linear discriminant analysis for classification of data streams , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[7] Rong Jin,et al. Scalable Kernel Clustering: Approximate Kernel k-means , 2014, ArXiv.
[8] Feiping Nie,et al. Trace Ratio Problem Revisited , 2009, IEEE Transactions on Neural Networks.
[9] Wai Keung Wong,et al. Deep Learning Regularized Fisher Mappings , 2011, IEEE Transactions on Neural Networks.
[10] Anastasios Tefas,et al. Class-Specific Kernel-Discriminant Analysis for Face Verification , 2007, IEEE Transactions on Information Forensics and Security.
[11] Xuesong Lu,et al. Fisher Discriminant Analysis With L1-Norm , 2014, IEEE Transactions on Cybernetics.
[12] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[13] Alexandros Iosifidis,et al. Class-Specific Reference Discriminant Analysis With Application in Human Behavior Analysis , 2015, IEEE Transactions on Human-Machine Systems.
[14] Alexandros Iosifidis,et al. Scaling Up Class-Specific Kernel Discriminant Analysis for Large-Scale Face Verification , 2016, IEEE Transactions on Information Forensics and Security.
[15] J KriegmanDavid,et al. Acquiring Linear Subspaces for Face Recognition under Variable Lighting , 2005 .
[16] Josef Kittler,et al. Class-Specific Kernel Fusion of Multiple Descriptors for Face Verification Using Multiscale Binarised Statistical Image Features , 2014, IEEE Transactions on Information Forensics and Security.
[17] Matthias W. Seeger,et al. Using the Nyström Method to Speed Up Kernel Machines , 2000, NIPS.
[18] Juan Carlos Niebles,et al. Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification , 2010, ECCV.
[19] Benjamin Recht,et al. Random Features for Large-Scale Kernel Machines , 2007, NIPS.
[20] Michael K. Ng,et al. Incremental Linear Discriminant Analysis: A Fast Algorithm and Comparisons , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[21] Takeo Kanade,et al. Comprehensive database for facial expression analysis , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).
[22] Jiwen Lu,et al. Automatic Subspace Learning via Principal Coefficients Embedding , 2014, IEEE Transactions on Cybernetics.
[23] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.
[24] Gene H. Golub,et al. Matrix computations (3rd ed.) , 1996 .
[25] KittlerJosef,et al. Class-Specific Kernel Fusion of Multiple Descriptors for Face Verification Using Multiscale Binarised Statistical Image Features , 2014 .
[26] Pong C. Yuen,et al. Incremental Linear Discriminant Analysis for Face Recognition , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[27] Anastasios Maronidis,et al. Subclass Graph Embedding and a Marginal Fisher Analysis paradigm , 2015, Pattern Recognit..
[28] Rasmus Pagh,et al. Fast and scalable polynomial kernels via explicit feature maps , 2013, KDD.
[29] C. Ding,et al. On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions , 2013, KDD.
[30] Ke Lu,et al. Low-Rank Discriminant Embedding for Multiview Learning , 2017, IEEE Transactions on Cybernetics.
[31] Cordelia Schmid,et al. Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).
[32] Andy Harter,et al. Parameterisation of a stochastic model for human face identification , 1994, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision.
[33] Alexandros Iosifidis,et al. Multi-view human movement recognition based on fuzzy distances and linear discriminant analysis , 2012, Comput. Vis. Image Underst..
[34] Shie Mannor,et al. The kernel recursive least-squares algorithm , 2004, IEEE Transactions on Signal Processing.
[35] Xuelong Li,et al. Graph Regularized Non-Negative Low-Rank Matrix Factorization for Image Clustering , 2017, IEEE Transactions on Cybernetics.
[36] Stan Z. Li,et al. Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition , 2016, IEEE Transactions on Cybernetics.
[37] David J. Kriegman,et al. Acquiring linear subspaces for face recognition under variable lighting , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] David G. Stork,et al. Pattern Classification (2nd ed.) , 1999 .
[39] Alexandros Iosifidis,et al. Kernel Reference Discriminant Analysis , 2014, Pattern Recognit. Lett..
[40] Michael J. Lyons,et al. Coding facial expressions with Gabor wavelets , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.
[41] André Stuhlsatz,et al. Feature Extraction With Deep Neural Networks by a Generalized Discriminant Analysis , 2012, IEEE Transactions on Neural Networks and Learning Systems.
[42] Jieping Ye,et al. Least squares linear discriminant analysis , 2007, ICML '07.
[43] Aleix M. Martínez,et al. Subclass discriminant analysis , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Stefanos Zafeiriou,et al. Regularized Kernel Discriminant Analysis With a Robust Kernel for Face Recognition and Verification , 2012, IEEE Transactions on Neural Networks and Learning Systems.
[45] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[46] G. F. Hughes,et al. On the mean accuracy of statistical pattern recognizers , 1968, IEEE Trans. Inf. Theory.
[47] Fadi Dornaika,et al. Exponential Local Discriminant Embedding and Its Application to Face Recognition , 2013, IEEE Transactions on Cybernetics.
[48] Alexandros Iosifidis,et al. Class-Specific Nonlinear Projections Using Class-Specific Kernel Spaces , 2015, 2015 IEEE Trustcom/BigDataSE/ISPA.
[49] Lawrence K. Saul,et al. Kernel Methods for Deep Learning , 2009, NIPS.
[50] G. W. Stewart,et al. Matrix Algorithms: Volume 1, Basic Decompositions , 1998 .
[51] Cordelia Schmid,et al. Actions in context , 2009, CVPR.
[52] Witold Pedrycz,et al. Incremental Hashing for Semantic Image Retrieval in Nonstationary Environments , 2017, IEEE Transactions on Cybernetics.
[53] Cordelia Schmid,et al. Action Recognition with Improved Trajectories , 2013, 2013 IEEE International Conference on Computer Vision.
[54] Nojun Kwak. Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick , 2017, IEEE Transactions on Cybernetics.
[55] Bin Xu,et al. Generalized Discriminant Analysis: A Matrix Exponential Approach , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[56] Nathan Halko,et al. Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions , 2009, SIAM Rev..
[57] Alexandros Iosifidis,et al. Graph Embedded Extreme Learning Machine , 2016, IEEE Transactions on Cybernetics.
[58] Alexandros Iosifidis,et al. Generalized Multi-View Embedding for Visual Recognition and Cross-Modal Retrieval , 2016, IEEE Transactions on Cybernetics.
[59] Jiawei Han,et al. Speed up kernel discriminant analysis , 2011, The VLDB Journal.