Using the proximal gradient and the accelerated proximal gradient as a canonical polyadic tensor decomposition algorithms in difficult situations
暂无分享,去创建一个
[1] Driss Aboutajdine,et al. CP decomposition approach to blind separation for DS-CDMA system using a new performance index , 2014, EURASIP J. Adv. Signal Process..
[2] R. Bro. PARAFAC. Tutorial and applications , 1997 .
[3] Pierre Comon,et al. ROBUST INDEPENDENT COMPONENT ANALYSIS , 2009 .
[4] L. Tucker,et al. Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.
[5] S. Leurgans,et al. A Decomposition for Three-Way Arrays , 1993, SIAM J. Matrix Anal. Appl..
[6] E. Lee,et al. APPLYING GRADIENT PROJECTION AND CONJUGATE GRADIENT TO THE OPTIMUM OPERATION OF RESERVOIRS1 , 1970 .
[7] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..
[8] Richard A. Harshman,et al. Determination and Proof of Minimum Uniqueness Conditions for PARAFAC1 , 1972 .
[9] P. Paatero. Construction and analysis of degenerate PARAFAC models , 2000 .
[10] Vin de Silva,et al. Tensor rank and the ill-posedness of the best low-rank approximation problem , 2006, math/0607647.
[11] Ben C. Mitchell,et al. Slowly converging parafac sequences: Swamps and two‐factor degeneracies , 1994 .
[12] J. Kruskal. Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics , 1977 .
[13] Michael Elad,et al. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[14] Richard A. Harshman,et al. Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis , 1970 .
[15] J. Chang,et al. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .
[16] Lieven De Lathauwer,et al. On the Uniqueness of the Canonical Polyadic Decomposition of Third-Order Tensors - Part I: Basic Results and Uniqueness of One Factor Matrix , 2013, SIAM J. Matrix Anal. Appl..
[17] F. L. Hitchcock. The Expression of a Tensor or a Polyadic as a Sum of Products , 1927 .
[18] J. Kruskal,et al. How 3-MFA data can cause degenerate parafac solutions, among other relationships , 1989 .
[19] Lieven De Lathauwer,et al. A Link between the Canonical Decomposition in Multilinear Algebra and Simultaneous Matrix Diagonalization , 2006, SIAM J. Matrix Anal. Appl..
[20] Caroline Fossati,et al. Denoising of Hyperspectral Images Using the PARAFAC Model and Statistical Performance Analysis , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[21] W. Rayens,et al. Two-factor degeneracies and a stabilization of PARAFAC , 1997 .
[22] Stephen P. Boyd,et al. Proximal Algorithms , 2013, Found. Trends Optim..
[23] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[24] Nikos D. Sidiropoulos,et al. Blind PARAFAC receivers for DS-CDMA systems , 2000, IEEE Trans. Signal Process..
[25] Pierre Comon,et al. Enhanced Line Search: A Novel Method to Accelerate PARAFAC , 2008, SIAM J. Matrix Anal. Appl..
[26] Na Li,et al. Some Convergence Results on the Regularized Alternating Least-Squares Method for Tensor Decomposition , 2011, 1109.3831.
[27] Li Zhang,et al. Global convergence of a modified Fletcher–Reeves conjugate gradient method with Armijo-type line search , 2006, Numerische Mathematik.
[28] H. Kiers. Towards a standardized notation and terminology in multiway analysis , 2000 .
[29] Margaret H. Wright,et al. Interior methods for constrained optimization , 1992, Acta Numerica.
[30] A. Geramita,et al. Ranks of tensors, secant varieties of Segre varieties and fat points , 2002 .
[31] A. Stegeman,et al. On Kruskal's uniqueness condition for the Candecomp/Parafac decomposition , 2007 .
[32] Jacek Gondzio,et al. Interior point methods 25 years later , 2012, Eur. J. Oper. Res..
[33] Tamara G. Kolda,et al. Tensor Decompositions and Applications , 2009, SIAM Rev..
[34] Patrick L. Combettes,et al. Proximal Splitting Methods in Signal Processing , 2009, Fixed-Point Algorithms for Inverse Problems in Science and Engineering.
[35] Rasmus Bro,et al. Improving the speed of multi-way algorithms:: Part I. Tucker3 , 1998 .
[36] Rasmus Bro,et al. A comparison of algorithms for fitting the PARAFAC model , 2006, Comput. Stat. Data Anal..
[37] Pierre Comon,et al. Blind Multilinear Identification , 2012, IEEE Transactions on Information Theory.
[38] R. Bro,et al. Fluorescence spectroscopy and multi-way techniques. PARAFAC , 2013 .
[39] B. Kowalski,et al. Tensorial resolution: A direct trilinear decomposition , 1990 .
[40] Pierre Comon,et al. Robust Independent Component Analysis by Iterative Maximization of the Kurtosis Contrast With Algebraic Optimal Step Size , 2010, IEEE Transactions on Neural Networks.
[41] Pierre Comon,et al. Tensors : A brief introduction , 2014, IEEE Signal Processing Magazine.
[42] Bijan Afsari,et al. Sensitivity Analysis for the Problem of Matrix Joint Diagonalization , 2008, SIAM J. Matrix Anal. Appl..
[43] E. Candès,et al. Sparsity and incoherence in compressive sampling , 2006, math/0611957.
[44] P. Comon,et al. Tensor decompositions, alternating least squares and other tales , 2009 .
[45] Souleymen Sahnoun,et al. Joint Source Estimation and Localization , 2015, IEEE Transactions on Signal Processing.
[46] Pierre Comon,et al. Coherence Constrained Alternating Least Squares , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).
[47] Rasmus Bro,et al. Improving the speed of multiway algorithms: Part II: Compression , 1998 .