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Fast optimization of non-negative matrix tri-factorization

Andrej Čopar, Blaž Zupan, Marinka Zitnik, Holger Fröhlich
2019 PLoS ONE  
Non-negative matrix tri-factorization (NMTF) is a popular technique for learning low-dimensional feature representation of relational data.  ...  Currently, NMTF learns a representation of a dataset through an optimization procedure that typically uses multiplicative update rules.  ...  In the case of non-negative matrix tri-factorization, the method realizes the non-negativity constraints by projecting negative values in a latent matrix to a non-negative space [43] .  ... 
doi:10.1371/journal.pone.0217994 pmid:31185054 pmcid:PMC6559648 fatcat:fow3izxa6jdarasm3khncmmlle

Stability of the Factor Structure of the Metabolic Syndrome across Pubertal Development: Confirmatory Factor Analyses of Three Alternative Models

Elizabeth Goodman, Chaoyang Li, Yu-Kang Tu, Earl Ford, Shumei S. Sun, Terry T.-K. Huang
2009 Journal of Pediatrics  
Models tested were a 1-factor model (A), a 4-factor model (B), and a secondorder latent factor model (C).  ...  Results-Convergence was achieved for all developmental stages for model A, but the fit was poor throughout (root mean square error of approximation > 0.1).  ...  Siervogel, PhD, at Lifespan Health Research Center, Department of Community Health, Wright State University School of Medicine, Dayton, Ohio, for his many contributions to the Fels Longitudinal Study.  ... 
doi:10.1016/j.jpeds.2009.04.045 pmid:19732562 pmcid:PMC3763727 fatcat:wbqiq3b4yzd43odfuk4oatc3pm

Second-order Symmetric Non-negative Latent Factor Analysis [article]

Weiling Li, Xin Luo
2022 arXiv   pre-print
The undirected network representation task can be efficiently addressed by a symmetry non-negative latent factor (SNLF) model, whose objective is clearly non-convex.  ...  Aiming at addressing this issue, this study proposes to incorporate an efficient second-order method into SNLF, thereby establishing a second-order symmetric non-negative latent factor analysis model for  ...  insight of SNLF model, the symmetric non-negative latent two-fold ideas: a) incorporating a mapping strategy into SNLF model factor models are proposed [12, 13].  ... 
arXiv:2203.02088v1 fatcat:qmrkbtn6zzhctnkpguka5belv4

Accelerated Parallel and Distributed Algorithm using Limited Internal Memory for Nonnegative Matrix Factorization [article]

Duy-Khuong Nguyen, Tu-Bao Ho
2015 arXiv   pre-print
The proposed algorithm takes advantages of both these algorithms to achieve a linear convergence rate of O(1-1/||Q||_2)^k in optimizing each factor matrix when fixing the other factor one in the sub-space  ...  Nonnegative matrix factorization (NMF) is a powerful technique for dimension reduction, extracting latent factors and learning part-based representation.  ...  Acknowledgement This work was supported by Asian Office of Aerospace R&D under agreement number FA2386-13-1-4046; and 911 Scholarship from Vietnam Ministry of Education and Training.  ... 
arXiv:1506.08938v1 fatcat:hnetbeqcxjgcrgl732gckhxkci

Accelerated parallel and distributed algorithm using limited internal memory for nonnegative matrix factorization

Duy Khuong Nguyen, Tu Bao Ho
2016 Journal of Global Optimization  
Keywords Non-negative matrix factorization · Accelerated anti-lopsided algorithm · Cooridinate descent algorithm · Parallel and distributed algorithm  ...  Nonnegative matrix factorization (NMF) is a powerful technique for dimension reduction, extracting latent factors and learning part-based representation.  ...  The authors declare that they have no conflict of interest.  ... 
doi:10.1007/s10898-016-0471-z fatcat:x6nyvaic5fhaxk5r7mf6hxvm6m

Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets [article]

Duy Khuong Nguyen, Tu Bao Ho
2016 arXiv   pre-print
In this paper, we propose a fast parallel randomized coordinate descent algorithm having fast convergence for large sparse datasets to archive sparse models and sparse representation.  ...  Specially, sparse models provide more concise understanding of the appearance of attributes over latent components, while sparse representation provides concise interpretability of the contribution of  ...  For example, spatially localized, parts-based subspace representation of visual patterns is learned by local non-negative matrix factorization with a localization constraint (LNMF) [8] .  ... 
arXiv:1604.04026v1 fatcat:ws237xmglfcuvaefqosfi733zi

Reproductive Strategy and Sexual Conflict Slow Life History Strategy Inihibts Negative Androcentrism

Paul R. Gladden, Aurelio José Figueredo, D. J. Andrejzak, Dan Nelson Jones, Vanessa Smith-Castro
2013 Journal of Methods and Measurement in the Social Sciences  
A structural model that the data fit well indicated a latent protective LH strategy trait predicted decreased negative androcentrism.  ...  , and emotional intelligence) and various convergent measures of Negative Androcentrism.  ...  Of the two latent constructs specified in our model, the Protective LH factor satisfies the second criterion for theoretical model identification, and the Negative Androcentrism factor satisfies both of  ... 
doi:10.2458/jmm.v4i1.17774 fatcat:5gevcyyokra2pcuziaft27fso4

Reproductive Strategy and Sexual Conflict Slow Life History Strategy Inihibts Negative Androcentrism

Paul R. Gladden, Aurelio José Figueredo, D. J. Andrejzak, Dan Nelson Jones, Vanessa Smith-Castro
2013 Journal of Methods and Measurement in the Social Sciences  
A structural model that the data fit well indicated a latent protective LH strategy trait predicted decreased negative androcentrism.  ...  , and emotional intelligence) and various convergent measures of Negative Androcentrism.  ...  Of the two latent constructs specified in our model, the Protective LH factor satisfies the second criterion for theoretical model identification, and the Negative Androcentrism factor satisfies both of  ... 
doi:10.2458/v4i1.17774 fatcat:36wezr6o5vcelbpfaxgmwa46ou

War and Peace: A Diachronic Social Biogeography of Life History Strategy and Between-Group Relations in Two Western European Populations

Aurelio José Figueredo, Mateo Peñaherrera-Aguirre, Heitor Barcellos Ferreira Fernandes, Sara Lindsey Lomayesva, Michael Anthony Woodley of Menie, Steven Charles Hertler, Matthew A. Sarraf
2019 Journal of Methods and Measurement in the Social Sciences  
In addition, a supplementary methodological objective was: (3) the convergent validation of diachronic lexicographic measures of LH strategy with respect to more traditional non-lexicographic indicators  ...  in the latent hierarchical structure of intelligence in Britannic populations, but as presently applied to the latent hierarchical structure of human LH strategy, now cross-validated in both Britannic  ...  In exploratory factor analysis one may count the number of non-salient factor loadings that would be fixed at zero upon cross-validation with a confirmatory factor model, and this number is referred to  ... 
doi:10.2458/v10i1.23522 fatcat:c6dtmjs2rvhlffwt3dcxviatse

PI-NLF: A Proportional-Integral Approach for Non-negative Latent Factor Analysis [article]

Ye Yuan, Xin Luo
2022 arXiv   pre-print
A non-negative latent factor (NLF) model performs efficient representation learning to an HDI matrix, whose learning process mostly relies on a single latent factor-dependent, non-negative and multiplicative  ...  Inspired by the prominent success of a proportional-integral (PI) controller in various applications, this paper proposes a Proportional-Integral-incorporated Non-negative Latent Factor (PI-NLF) model  ...  To implement convenient and efficient non-negative latent factor analysis on an HDI matrix, Luo et al.  ... 
arXiv:2205.02591v1 fatcat:buk6zui4fngrdm7g44dgsnl7fu

The Growth Path of Agricultural Labor Productivity in China: A Latent Growth Curve Model at the Prefectural Level

Peng Bin, Marco Vassallo
2016 Economies  
Based on a balanced panel data containing 287 Chinese prefectures from 2000 to 2013, this study applies the Latent Growth Curve Model (LGCM) and finds that the agricultural labor productivity follows a  ...  Further statistical analysis shows an expanding gap of agricultural labor productivity among different Chinese prefectures.  ...  Acknowledgments: The first author thanks the financial support received through the project Cambiamento istituzionale, crescita economica e sviluppo sociale funded by the autonomous Province of Trento.  ... 
doi:10.3390/economies4030013 fatcat:shqjfnqsdbf3bgjukw4fbywno4

On the Convergence of Bound Optimization Algorithms [article]

Ruslan R Salakhutdinov, Sam T Roweis, Zoubin Ghahramani
2012 arXiv   pre-print
We derive a general relationship between the updates performed by bound optimization methods and those of gradient and second-order methods and identify analytic conditions under which bound optimization  ...  We report empirical results supporting our analysis and showing that simple data preprocessing can result in dramatically improved performance of bound optimizers in practice.  ...  Non-Negative Matrix Factorization (NMF) Given a non-negative matrix V, the NMF algorithm [3] tries to find matrices W and H, such that V � W H.  ... 
arXiv:1212.2490v1 fatcat:sq5iprry35e5biytseenc4n3k4

Validity of the Center for Epidemiologic Studies Depression Scale (CES-D) in Eritrean refugees living in Ethiopia

Berhanie Getnet, Atalay Alem
2019 BMJ Open  
These two latent factors have a weaker standardised covariance estimate of 33% (24% for women and 40% for men), demonstrating evidence of discriminant validity.  ...  , p<0.001), FAST (r=0.197, p<0.001) and emotion-oriented coping (r=0.096, p˂0.05) providing evidence of its convergent validity.  ...  He also led the validation of measures, data collection, analysis, interpretation and wrote the findings.  ... 
doi:10.1136/bmjopen-2018-026129 pmid:31064806 pmcid:PMC6528005 fatcat:dfogktqeh5aqhmjcpcpzuxbfau

Parallel Algorithms for Constrained Tensor Factorization via Alternating Direction Method of Multipliers

Athanasios P. Liavas, Nicholas D. Sidiropoulos
2015 IEEE Transactions on Signal Processing  
A new constrained tensor factorization framework is proposed in this paper, building upon the Alternating Direction method of Multipliers (ADMoM).  ...  Tensor factorization has proven useful in a wide range of applications, from sensor array processing to communications, speech and audio signal processing, and machine learning.  ...  NON-NEGATIVE TENSOR FACTORIZATION Let tensor admit a non-negative 3 CP decomposition of order where , , and .  ... 
doi:10.1109/tsp.2015.2454476 fatcat:z2yhxvgnibd57ne2dkd2hwqhvi

A common spatial factor analysis model for measured neighborhood-level characteristics: The Multi-Ethnic Study of Atherosclerosis

Rachel C. Nethery, Joshua L. Warren, Amy H. Herring, Kari A.B. Moore, Kelly R. Evenson, Ana V. Diez-Roux
2015 Health and Place  
A common spatial factor analysis model in the Bayesian setting was utilized in order to properly characterize dependencies in the data.  ...  Results suggest that use of the spatial factor model can result in more precise estimation of factor scores, improved insight into the spatial patterns in the data, and the ability to more accurately assess  ...  A full list of participating MESA investigators and institutions can be found at http://www.mesanhlbi.org.  ... 
doi:10.1016/j.healthplace.2015.08.009 pmid:26372887 pmcid:PMC4679666 fatcat:mausnqs5wjdq5eeznddo2h2zfm
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