IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v79y2017i3p899-916.html
   My bibliography  Save this article

Provable sparse tensor decomposition

Author

Listed:
  • Will Wei Sun
  • Junwei Lu
  • Han Liu
  • Guang Cheng

Abstract

No abstract is available for this item.

Suggested Citation

  • Will Wei Sun & Junwei Lu & Han Liu & Guang Cheng, 2017. "Provable sparse tensor decomposition," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 899-916, June.
  • Handle: RePEc:bla:jorssb:v:79:y:2017:i:3:p:899-916
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssb.12190
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J. Carroll & Jih-Jie Chang, 1970. "Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 283-319, September.
    2. Hua Zhou & Lexin Li & Hongtu Zhu, 2013. "Tensor Regression with Applications in Neuroimaging Data Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 540-552, June.
    3. Joseph Kruskal, 1976. "More factors than subjects, tests and treatments: An indeterminacy theorem for canonical decomposition and individual differences scaling," Psychometrika, Springer;The Psychometric Society, vol. 41(3), pages 281-293, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xianpeng Mao & Yuning Yang, 2022. "Several approximation algorithms for sparse best rank-1 approximation to higher-order tensors," Journal of Global Optimization, Springer, vol. 84(1), pages 229-253, September.
    2. Li, Gen, 2020. "Generalized Co-clustering Analysis via Regularized Alternating Least Squares," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    3. Shi, Chengchun & Lu, Wenbin & Song, Rui, 2019. "Determining the number of latent factors in statistical multi-relational learning," LSE Research Online Documents on Economics 102110, London School of Economics and Political Science, LSE Library.
    4. Yuefeng Han & Dan Yang & Cun-Hui Zhang & Rong Chen, 2021. "CP Factor Model for Dynamic Tensors," Papers 2110.15517, arXiv.org, revised Apr 2024.
    5. Mao, Xianpeng & Yang, Yuning, 2022. "Best sparse rank-1 approximation to higher-order tensors via a truncated exponential induced regularizer," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    6. Chang, Jinyuan & Zhang, Henry & Yang, Lin & Yao, Qiwei, 2023. "Modelling matrix time series via a tensor CP-decomposition," LSE Research Online Documents on Economics 117644, London School of Economics and Political Science, LSE Library.
    7. Carlos Martin-Barreiro & John A. Ramirez-Figueroa & Ana B. Nieto-Librero & Víctor Leiva & Ana Martin-Casado & M. Purificación Galindo-Villardón, 2021. "A New Algorithm for Computing Disjoint Orthogonal Components in the Three-Way Tucker Model," Mathematics, MDPI, vol. 9(3), pages 1-22, January.
    8. Ke, Baofang & Zhao, Weihua & Wang, Lei, 2023. "Smoothed tensor quantile regression estimation for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Willem Kloot & Pieter Kroonenberg, 1985. "External analysis with three-mode principal component models," Psychometrika, Springer;The Psychometric Society, vol. 50(4), pages 479-494, December.
    2. Josep Patau & Antonio Somoza & Salvador Torra, 2020. "Diagnosis of the Domino Effect in Bankruptcy Situations Through Positioning Maps and Their Evolution 10 Years Later," SAGE Open, , vol. 10(4), pages 21582440209, December.
    3. Monica Billio & Roberto Casarin & Matteo Iacopini & Sylvia Kaufmann, 2023. "Bayesian Dynamic Tensor Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 429-439, April.
    4. Richard Harshman & Margaret Lundy, 1996. "Uniqueness proof for a family of models sharing features of Tucker's three-mode factor analysis and PARAFAC/candecomp," Psychometrika, Springer;The Psychometric Society, vol. 61(1), pages 133-154, March.
    5. Vivek F. Farias & Andrew A. L, 2019. "Learning Preferences with Side Information," Management Science, INFORMS, vol. 65(7), pages 3131-3149, July.
    6. Rungang Han & Yuetian Luo & Miaoyan Wang & Anru R. Zhang, 2022. "Exact clustering in tensor block model: Statistical optimality and computational limit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1666-1698, November.
    7. Mariela González-Narváez & María José Fernández-Gómez & Susana Mendes & José-Luis Molina & Omar Ruiz-Barzola & Purificación Galindo-Villardón, 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    8. Lin Liu, 2021. "Matrix‐based introduction to multivariate data analysis, by KoheiAdachi 2nd edition. Singapore: Springer Nature, 2020. pp. 457," Biometrics, The International Biometric Society, vol. 77(4), pages 1498-1500, December.
    9. S. Hess & E. Suárez & J. Camacho & G. Ramírez & B. Hernández, 2001. "Reliability of Coordinates Obtained by MINISSA Concerning the Order of Presented Stimuli," Quality & Quantity: International Journal of Methodology, Springer, vol. 35(2), pages 117-128, May.
    10. Cui Guo & Jian Kang & Timothy D. Johnson, 2022. "A spatial Bayesian latent factor model for image‐on‐image regression," Biometrics, The International Biometric Society, vol. 78(1), pages 72-84, March.
    11. Wedel, M. & Bijmolt, T.H.A., 1998. "Mixed Tree and Spatial Representation of Dissimilarity Judgments," Discussion Paper 1998-109, Tilburg University, Center for Economic Research.
    12. Henk Kiers, 1991. "Hierarchical relations among three-way methods," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 449-470, September.
    13. Pietro Amenta & Antonio Lucadamo & Antonello D’Ambra, 2021. "Restricted Common Component and Specific Weight Analysis: A Constrained Explorative Approach for the Customer Satisfaction Evaluation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 409-427, August.
    14. Elizabeth Hellier & Kirsteen Aldrich & Daniel B. Wright & Denny Daunt & Judy Edworthy, 2007. "A Multi Dimensional Analysis of Warning Signal Words," Journal of Risk Research, Taylor & Francis Journals, vol. 10(3), pages 323-338, April.
    15. Stegeman, Alwin & Ten Berge, Jos M.F., 2006. "Kruskal's condition for uniqueness in Candecomp/Parafac when ranks and k-ranks coincide," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 210-220, January.
    16. Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    17. Jad Beyhum & Eric Gautier, 2020. "Factor and factor loading augmented estimators for panel regression," Working Papers hal-02957008, HAL.
    18. Viet-Thi Tran & Mariam Mama Djima & Eugene Messou & Jocelyne Moisan & Jean-Pierre Grégoire & Didier K Ekouevi, 2018. "Avoidable workload of care for patients living with HIV infection in Abidjan, Côte d’Ivoire: A cross-sectional study," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-15, August.
    19. Douglas Clarkson & Richard Gonzalez, 2001. "Random effects diagonal metric multidimensional scaling models," Psychometrika, Springer;The Psychometric Society, vol. 66(1), pages 25-43, March.
    20. Rolf Langeheine, 1982. "Statistical evaluation of measures of fit in the Lingoes-Borg procrustean individual differences scaling," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 427-442, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssb:v:79:y:2017:i:3:p:899-916. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.