Stochastic Gradients for Large-Scale Tensor Decomposition.

Kolda, Tamara G.; Hong, David

doi:10.1137/19M1266265

Stochastic Gradients for Large-Scale Tensor Decomposition.

Conference · Fri Jan 31 23:00:00 EST 2020

DOI:https://doi.org/10.1137/19M1266265· OSTI ID:1767900

Kolda, Tamara G.; Hong, David

Abstract not provided.

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Research Organization:: Sandia National Laboratories (SNL-CA), Livermore, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

DOE Contract Number:: AC04-94AL85000

OSTI ID:: 1767900

Report Number(s):: SAND2020-2247C; 684214

Country of Publication:: United States

Language:: English

References (26)

A Practical Randomized CP Tensor Decomposition Battaglino, Casey; Ballard, Grey; Kolda, Tamara G. SIAM Journal on Matrix Analysis and Applications, Vol. 39, Issue 2 https://doi.org/10.1137/17m1112303	journal	January 2018
On the performance of gas sensor arrays in open sampling systems using Inhibitory Support Vector Machines Vergara, Alexander; Fonollosa, Jordi; Mahiques, Jonas Sensors and Actuators B: Chemical, Vol. 185 https://doi.org/10.1016/j.snb.2013.05.027	journal	August 2013
A scalable optimization approach for fitting canonical tensor decompositions Acar, Evrim; Dunlavy, Daniel M.; Kolda, Tamara G. Journal of Chemometrics, Vol. 25, Issue 2 https://doi.org/10.1002/cem.1335	journal	January 2011
Tensor Decompositions and Applications Kolda, Tamara G.; Bader, Brett W. SIAM Review, Vol. 51, Issue 3 https://doi.org/10.1137/07070111X	journal	August 2009
Computational Advertising: Techniques for Targeting Relevant Ads Woodruff, David P. Foundations and Trends® in Theoretical Computer Science, Vol. 10, Issue 1-2 https://doi.org/10.1561/0400000060	journal	January 2014
Positive tensor factorization Welling, Max; Weber, Markus Pattern Recognition Letters, Vol. 22, Issue 12 https://doi.org/10.1016/S0167-8655(01)00070-8	journal	October 2001
Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors Mardani, Morteza; Mateos, Gonzalo; Giannakis, Georgios B. IEEE Transactions on Signal Processing, Vol. 63, Issue 10 https://doi.org/10.1109/TSP.2015.2417491	journal	May 2015
Matrix Factorization Techniques for Recommender Systems Koren, Yehuda; Bell, Robert; Volinsky, Chris Computer, Vol. 42, Issue 8 https://doi.org/10.1109/MC.2009.263	journal	August 2009
Analysis of longitudinal metabolomics data Jansen, J. J.; Hoefsloot, H. C. J.; Boelens, H. F. M. Bioinformatics, Vol. 20, Issue 15 https://doi.org/10.1093/bioinformatics/bth268	journal	April 2004
Generalized Low Rank Models Udell, Madeleine; Horn, Corinne; Zadeh, Reza Foundations and Trends® in Machine Learning, Vol. 9, Issue 1 https://doi.org/10.1561/2200000055	journal	January 2016
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm Needell, Deanna; Srebro, Nathan; Ward, Rachel Mathematical Programming, Vol. 155, Issue 1-2 https://doi.org/10.1007/s10107-015-0864-7	journal	February 2015
Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition Carroll, J. Douglas; Chang, Jih-Jie Psychometrika, Vol. 35, Issue 3 https://doi.org/10.1007/BF02310791	journal	September 1970
A Limited Memory Algorithm for Bound Constrained Optimization Byrd, Richard H.; Lu, Peihuang; Nocedal, Jorge SIAM Journal on Scientific Computing, Vol. 16, Issue 5 https://doi.org/10.1137/0916069	journal	September 1995
Software for Sparse Tensor Decomposition on Emerging Computing Architectures Phipps, Eric T.; Kolda, Tamara G. SIAM Journal on Scientific Computing, Vol. 41, Issue 3 https://doi.org/10.1137/18M1210691	journal	January 2019
Statistically weighted principal component analysis of rapid scanning wavelength kinetics experiments Cochran, Robert N.; Horne, Frederick H. Analytical Chemistry, Vol. 49, Issue 6 https://doi.org/10.1021/ac50014a045	journal	May 1977
Correcting systematic effects in a large set of photometric light curves Tamuz, O.; Mazeh, T.; Zucker, S. Monthly Notices of the Royal Astronomical Society, Vol. 356, Issue 4 https://doi.org/10.1111/j.1365-2966.2004.08585.x	journal	February 2005
A Practical Randomized CP Tensor Decomposition Battaglino, Casey; Ballard, Grey; Kolda, Tamara G. SIAM Journal on Matrix Analysis and Applications, Vol. 39, Issue 2 https://doi.org/10.1137/17M1112303	journal	January 2018
A Randomized Block Sampling Approach to Canonical Polyadic Decomposition of Large-Scale Tensors Vervliet, Nico; De Lathauwer, Lieven IEEE Journal of Selected Topics in Signal Processing, Vol. 10, Issue 2 https://doi.org/10.1109/JSTSP.2015.2503260	journal	March 2016
On Tensors, Sparsity, and Nonnegative Factorizations Chi, Eric C.; Kolda, Tamara G. SIAM Journal on Matrix Analysis and Applications, Vol. 33, Issue 4 https://doi.org/10.1137/110859063	journal	January 2012
A Scalable Generative Graph Model with Community Structure Kolda, Tamara G.; Pinar, Ali; Plantenga, Todd SIAM Journal on Scientific Computing, Vol. 36, Issue 5 https://doi.org/10.1137/130914218	journal	January 2014
Generalized Canonical Polyadic Tensor Decomposition Hong, David; Kolda, Tamara G.; Duersch, Jed A. SIAM Review, Vol. 62, Issue 1 https://doi.org/10.1137/18M1203626	journal	January 2020
Scalable tensor factorizations for incomplete data Acar, Evrim; Dunlavy, Daniel M.; Kolda, Tamara G. Chemometrics and Intelligent Laboratory Systems, Vol. 106, Issue 1 https://doi.org/10.1016/j.chemolab.2010.08.004	journal	March 2011
Efficient MATLAB Computations with Sparse and Factored Tensors Bader, Brett W.; Kolda, Tamara G. SIAM Journal on Scientific Computing, Vol. 30, Issue 1 https://doi.org/10.1137/060676489	journal	January 2008
Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations Hansen, Samantha; Plantenga, Todd; Kolda, Tamara G. Optimization Methods and Software, Vol. 30, Issue 5 https://doi.org/10.1080/10556788.2015.1009977	journal	February 2015
Adaptive Algorithms to Track the PARAFAC Decomposition of a Third-Order Tensor Nion, D.; Sidiropoulos, N. D. IEEE Transactions on Signal Processing, Vol. 57, Issue 6 https://doi.org/10.1109/TSP.2009.2016885	journal	June 2009
Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations Phan, Anh-Huy; Tichavsky, Petr; Cichocki, Andrzej IEEE Transactions on Signal Processing, Vol. 61, Issue 19 https://doi.org/10.1109/TSP.2013.2269903	journal	October 2013

Cited By (1)

Practical Leverage-Based Sampling for Low-Rank Tensor Decomposition Larsen, Brett W.; Kolda, Tamara G. arXiv https://doi.org/10.48550/arxiv.2006.16438	preprint	January 2020

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