Data matrix

Results: 1829



#Item
11

Backend Decision Making Matrix BaaS OR DIY? Your App requires simple data retrieval/storage. Your App requires custom backend

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Source URL: ausios.com

- Date: 2016-08-11 06:32:58
    12

    Collective Matrix Factorization Hashing for Multimodal Data Guiguang Ding Yuchen Guo Jile Zhou School of Software,Tsinghua University, Beijing, P.R.China

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    Source URL: ise.thss.tsinghua.edu.cn

    - Date: 2014-07-28 02:51:54
      13

      Overland Storage / Tandberg Data Software Compatibility Matrix EFFECTIVE: December 2016 Software Compatibility Matrix EFFECTIVE: December 2016

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      Source URL: www.overlandstorage.com

      - Date: 2016-12-12 14:23:54
        14

        -Why use SLE?Simple Off-line Clean-up Techniques to Eliminate Phospholipids and other Matrix Interferences in LC-MS/MS Bioanalysis ＜＜2015年11月14日：薬物動態学会年会 ランチョンセミナー＞＞

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        Source URL: data.biotage.co.jp

        - Date: 2016-01-19 00:25:00
          15

          Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information Changwei Hu1 Piyush Rai12 Lawrence Carin1

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          Source URL: www.cse.iitk.ac.in

          - Date: 2016-04-10 07:53:19
            16

            The Compressed Annotation Matrix: An Efficient Data Structure for Computing Persistent Cohomology Jean-Daniel Boissonnat & Tamal Dey & Cl´ement Maria JGA 2013

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            Source URL: quentin.mrgt.fr

            - Date: 2014-01-09 09:41:45
              17

              Data Compression, 4th Edition. Program and Pseudo-Code Listings (Advise the author about missing or bad listings.) Chapter 1 % Returns the run lengths of % a matrix of 0s and 1s

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              Source URL: www.davidsalomon.name

              - Date: 2006-08-30 20:56:00
                18

                Optimal CUR Matrix Decompositions Christos Boutsidis1 Yahoo! Labs New York David P. Woodruff 2

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                Source URL: mmds-data.org

                - Date: 2014-06-24 18:17:18
                  19

                  We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit

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                  Source URL: mmds-data.org

                  - Date: 2016-06-23 15:50:48
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