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Dimension theory
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21	Bar Widths and the Spaces in Between Stephen Few, Perceptual Edge Visual Business Intelligence Newsletter July/August/SeptemberA bar in a bar graph encodes a single value by varying its size in one dimension only: Add to Reading List Source URL: www.perceptualedge.com Language: English - Date: 2016-07-12 13:35:47 Graph Graph theory Bar chart Topological graph theory Bar Data visualization Information Computing
22	Neural Word Embedding as Implicit Matrix Factorization Omer Levy Department of Computer Science Bar-Ilan University Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-12-02 20:43:40 Algebra Linear algebra Mathematics Numerical linear algebra Matrix theory Singular value decomposition Dimension reduction Matrix Low-rank approximation Singular value Pointwise mutual information Factorization
23	Sampling-based Data Mining Algorithms: Modern Techniques and Case Studies Matteo Riondato Brown University, Providence, RI 02912, USA Abstract. Sampling a dataset for faster analysis and looking at it Add to Reading List Source URL: matteo.rionda.to Language: English - Date: 2016-07-30 12:22:15 Mathematics Graph theory Network theory Theoretical computer science Computational learning theory Dimension Statistical classification VC dimension Centrality Sampling Statistics Mode
24	A MDL4BMF: Minimum Description Length for Boolean Matrix Factorization PAULI MIETTINEN, Max-Planck Institute for Informatics JILLES VREEKEN, Max-Planck Institute for Informatics, Saarland University, University of Antwer Add to Reading List Source URL: people.mpi-inf.mpg.de Language: English - Date: 2014-05-09 10:45:37 Algebra Mathematics Linear algebra Matrix theory Numerical linear algebra Multivariate statistics Dimension reduction Non-negative matrix factorization Matrix Singular value decomposition Principal component analysis Factorization
25	Chain minors are FPT Jaroslaw Blasiok1 and Marcin Kami´ nski2 1 Instytut Informatyki Add to Reading List Source URL: rutcor.rutgers.edu Language: English Computational complexity theory Theory of computation Analysis of algorithms Order theory Parameterized complexity NP Exponential time hypothesis Randomized algorithm Time complexity Partially ordered set Order dimension
26	AG-SEMINAR WS: ∞-CATEGORIES AND THEIR APPLICATIONS MORITZ GROTH AND GEORGIOS RAPTIS The aim of higher category theory is to develop a theory of ‘categories with morphisms of arbitrarily high dimension’ that Add to Reading List Source URL: www.math.uni-bonn.de Language: English - Date: 2011-10-16 11:41:31 Algebra Mathematics Abstract algebra Category theory Homotopy theory Homological algebra Functors Algebraic geometry Model category Simplicial set Andr Joyal Higher category theory
27	ALGORITHMIC LINEAR DIMENSION REDUCTION IN THE `1 NORM FOR SPARSE VECTORS A. C. GILBERT, M. J. STRAUSS, J. A. TROPP, AND R. VERSHYNIN Abstract. We can recover approximately a sparse signal with limited noise, i.e, a vecto Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2009-02-03 14:30:47 Digital signal processing Computational complexity theory Matrix Fast Fourier transform Time complexity Mathematics Computer science Theoretical computer science Polynomials
28	Fractal Working Group 1 Coordinators: Gerald Edgar, Larry Lindsay Notes LaTeX-ed in real-time by Steven Miller Participants: Bruce Adcock, Youri Dimitrov, Gerald Edgar, Dean Eiger, Charles Estill, Larry Lindsay, Steven M Add to Reading List Source URL: web.williams.edu Language: English - Date: 2004-01-11 12:28:39 Fractals Mathematics Mathematical analysis Dimension theory Geometry Metric geometry Topological spaces Measure theory Hausdorff dimension MinkowskiBouligand dimension Hausdorff measure Fractal
29	Proceedings of ARPA Image Understanding Workshop Monterey, NovemberSoftware Library for Appearance Matching (SLAM) * Sameer A. Nene, Shree K. Nayar and Hiroshi Murase Center for Research in Intelligent Systems, De Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2005-07-11 00:33:12 Algebra Mathematics Linear algebra Dimension reduction Multivariate statistics Matrix theory Machine learning Eigenvalues and eigenvectors Vector space Principal component analysis Eigenface Pattern recognition
30	REVlEW The Vapnik-Chervonenkis Dimension: Information versus Complexity in Learning Yaser S. Abu-Mostafa California Institute of Terhnohgy, Pasadcna, CAUSA Add to Reading List Source URL: authors.library.caltech.edu Language: English - Date: 2012-12-26 05:25:09 Computational learning theory Machine learning Learning Mathematics Cognition Statistical classification Empirical process VC dimension Probability distribution Artificial neural network NIP Uniform convergence

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