Parallel Algorithms for Constrained Tensor Factorization via Alternating Direction Method of Multipliers
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[1] L. Tucker,et al. Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.
[2] Tamara G. Kolda,et al. Efficient MATLAB Computations with Sparse and Factored Tensors , 2007, SIAM J. Sci. Comput..
[3] Rasmus Bro,et al. Multi-way Analysis with Applications in the Chemical Sciences , 2004 .
[4] J. Kruskal. Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics , 1977 .
[5] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[6] Daniel M. Dunlavy,et al. A scalable optimization approach for fitting canonical tensor decompositions , 2011 .
[7] Lieven De Lathauwer,et al. Decompositions of a Higher-Order Tensor in Block Terms - Part II: Definitions and Uniqueness , 2008, SIAM J. Matrix Anal. Appl..
[8] David E. Booth,et al. Multi-Way Analysis: Applications in the Chemical Sciences , 2005, Technometrics.
[9] Rasmus Bro,et al. A comparison of algorithms for fitting the PARAFAC model , 2006, Comput. Stat. Data Anal..
[10] Tamara G. Kolda,et al. Scalable Tensor Decompositions for Multi-aspect Data Mining , 2008, 2008 Eighth IEEE International Conference on Data Mining.
[11] Nikos D. Sidiropoulos,et al. Blind PARAFAC receivers for DS-CDMA systems , 2000, IEEE Trans. Signal Process..
[12] Bo Yu,et al. An alternating direction and projection algorithm for structure-enforced matrix factorization , 2017, Comput. Optim. Appl..
[13] Nikos D. Sidiropoulos,et al. A parallel algorithm for big tensor decomposition using randomly compressed cubes (PARACOMP) , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[14] Christopher J. Hillar,et al. Most Tensor Problems Are NP-Hard , 2009, JACM.
[15] Andrzej Cichocki,et al. Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis , 2014, IEEE Signal Processing Magazine.
[16] Yin Zhang,et al. An alternating direction algorithm for matrix completion with nonnegative factors , 2011, Frontiers of Mathematics in China.
[17] Peter J. Haas,et al. Large-scale matrix factorization with distributed stochastic gradient descent , 2011, KDD.
[18] J. T. ten Berge,et al. The link between sufficient conditions by Harshman and by Kruskal for uniqueness in Candecomp/Parafac , 2009 .
[19] André Lima Férrer de Almeida,et al. Distributed large-scale tensor decomposition , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[20] Alexey Ozerov,et al. Notes on Nonnegative Tensor Factorization of the Spectrogram for Audio Source Separation: Statistical Insights and Towards Self-Clustering of the Spatial Cues , 2010, CMMR.
[21] Richard A. Harshman,et al. Determination and Proof of Minimum Uniqueness Conditions for PARAFAC1 , 1972 .
[22] Rasmus Bro,et al. The N-way Toolbox for MATLAB , 2000 .
[23] P. Kroonenberg. Applied Multiway Data Analysis , 2008 .
[24] Nikos D. Sidiropoulos,et al. ParCube: Sparse Parallelizable Tensor Decompositions , 2012, ECML/PKDD.
[25] J. Chang,et al. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .
[26] Nikos D. Sidiropoulos,et al. Parallel Randomly Compressed Cubes : A scalable distributed architecture for big tensor decomposition , 2014, IEEE Signal Processing Magazine.
[27] André Lima Férrer de Almeida,et al. Distributed computation of tensor decompositions in collaborative networks , 2013, 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).
[28] Lieven De Lathauwer,et al. Optimization-Based Algorithms for Tensor Decompositions: Canonical Polyadic Decomposition, Decomposition in Rank-(Lr, Lr, 1) Terms, and a New Generalization , 2013, SIAM J. Optim..
[29] Giorgio Ottaviani,et al. On Generic Identifiability of 3-Tensors of Small Rank , 2011, SIAM J. Matrix Anal. Appl..
[30] Nikos D. Sidiropoulos,et al. Batch and Adaptive PARAFAC-Based Blind Separation of Convolutive Speech Mixtures , 2010, IEEE Transactions on Audio, Speech, and Language Processing.
[31] Richard A. Harshman,et al. Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis , 1970 .
[32] Sanjay Ghemawat,et al. MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.
[33] Nikos D. Sidiropoulos,et al. Parallel factor analysis in sensor array processing , 2000, IEEE Trans. Signal Process..
[34] Tamara G. Kolda,et al. Tensor Decompositions and Applications , 2009, SIAM Rev..
[35] Nikos D. Sidiropoulos,et al. Memory-efficient parallel computation of tensor and matrix products for big tensor decomposition , 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.
[36] Nikos D. Sidiropoulos,et al. Parallel algorithms for large scale constrained tensor decomposition , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[37] Christos Faloutsos,et al. GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries , 2012, KDD.