Online tensor methods for learning latent variable models
暂无分享,去创建一个
Anima Anandkumar | Furong Huang | U. N. Niranjan | Mohammad Umar Hakeem | Anima Anandkumar | Furong Huang | U. Niranjan | Furong Huang
[1] M. McPherson,et al. Birds of a Feather: Homophily in Social Networks , 2001 .
[2] Sujay Sanghavi,et al. Clustering Sparse Graphs , 2012, NIPS.
[3] Edoardo M. Airoldi,et al. Mixed Membership Stochastic Blockmodels , 2007, NIPS.
[4] B. Fadem. High-yield behavioral science / , 2013 .
[5] David M Blei,et al. Efficient discovery of overlapping communities in massive networks , 2013, Proceedings of the National Academy of Sciences.
[6] Korbinian Strimmer,et al. fdrtool: a versatile R package for estimating local and tail area-based false discovery rates , 2008, Bioinform..
[7] Jure Leskovec,et al. Defining and evaluating network communities based on ground-truth , 2012, Knowledge and Information Systems.
[8] Matthieu Latapy,et al. Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..
[9] Tze Meng Low,et al. Exploiting Symmetry in Tensors for High Performance: Multiplication with Symmetric Tensors , 2013, SIAM J. Sci. Comput..
[10] Mason A. Porter,et al. Comparing Community Structure to Characteristics in Online Collegiate Social Networks , 2008, SIAM Rev..
[11] Andrea Lancichinetti,et al. Detecting the overlapping and hierarchical community structure in complex networks , 2008, 0802.1218.
[12] Anima Anandkumar,et al. Tensor Decompositions for Learning Latent Variable Models (A Survey for ALT) , 2015, ALT.
[13] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.
[14] Dit-Yan Yeung,et al. Overlapping community detection via bounded nonnegative matrix tri-factorization , 2012, KDD.
[15] H. Kushner,et al. Stochastic Approximation and Recursive Algorithms and Applications , 2003 .
[16] Michael J. Freedman,et al. Scalable Inference of Overlapping Communities , 2012, NIPS.
[17] Dan Feldman,et al. Turning big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering , 2013, SODA.
[18] R. Sokal,et al. THE COMPARISON OF DENDROGRAMS BY OBJECTIVE METHODS , 1962 .
[19] David F. Gleich,et al. Tall and skinny QR factorizations in MapReduce architectures , 2011, MapReduce '11.
[20] Andrea Lancichinetti,et al. Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.
[21] T. Nepusz,et al. Fuzzy communities and the concept of bridgeness in complex networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[22] Ankur Narang,et al. Fast Community Detection Algorithm with GPUs and Multicore Architectures , 2011, 2011 IEEE International Parallel & Distributed Processing Symposium.
[23] Tamara G. Kolda,et al. Efficiently Computing Tensor Eigenvalues on a GPU , 2011, 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum.
[24] Ruslan Salakhutdinov,et al. Bayesian probabilistic matrix factorization using Markov chain Monte Carlo , 2008, ICML '08.
[25] Michael W. Mahoney,et al. Revisiting the Nystrom Method for Improved Large-scale Machine Learning , 2013, J. Mach. Learn. Res..
[26] Tze Meng Low,et al. Exploiting Symmetry in Tensors for High Performance , 2013, ArXiv.
[27] Ruslan Salakhutdinov,et al. Probabilistic Matrix Factorization , 2007, NIPS.
[28] David M. Blei,et al. Probabilistic topic models , 2012, Commun. ACM.
[29] J. Moreno. Who Shall Survive: A New Approach to the Problem of Human Interrelations , 2017 .
[30] John Langford,et al. An objective evaluation criterion for clustering , 2004, KDD.
[31] Frank McSherry,et al. Spectral partitioning of random graphs , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.
[32] E. Oja,et al. On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix , 1985 .
[33] David P. Woodruff,et al. Low rank approximation and regression in input sparsity time , 2013, STOC '13.
[34] A. Heinson. Single Top Quarks at the Tevatron , 2008, 0809.0960.
[35] Anima Anandkumar,et al. A Tensor Spectral Approach to Learning Mixed Membership Community Models , 2013, COLT.
[36] Joel A. Tropp,et al. Robust Computation of Linear Models by Convex Relaxation , 2012, Foundations of Computational Mathematics.
[37] Nathan Srebro,et al. Stochastic optimization for PCA and PLS , 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[38] Mark E. J. Newman,et al. Stochastic blockmodels and community structure in networks , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.
[39] Joseph JáJá,et al. An Introduction to Parallel Algorithms , 1992 .
[40] S. Sitharama Iyengar,et al. Introduction to parallel algorithms , 1998, Wiley series on parallel and distributed computing.
[41] Santosh S. Vempala,et al. Principal Component Analysis and Higher Correlations for Distributed Data , 2013, COLT.
[42] Michael W. Berry,et al. SVDPACKC (Version 1.0) User''s Guide , 1993 .
[43] Joseph M. Hellerstein,et al. GraphLab: A New Framework For Parallel Machine Learning , 2010, UAI.