Multi Kernel Classification Machine Universum by Zhu Changming (9 results)

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    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

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      Seller: Books Puddle, New York, NY, U.S.A.Books Puddle

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    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

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      Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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      Paperback. Condition: Brand New. 56 pages. 8.66x5.91x0.13 inches. In Stock.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

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      Taschenbuch. Condition: Neu. Multi-kernel Classification Machine with Universum learning | Changming Zhu | Taschenbuch | 56 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659707933 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Language: English

      Published by LAP LAMBERT Academic Publishing Mrz 2017, 2017

      3659707937 / 9783659707933

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      Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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      Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Universum learning can reflect priori knowledge about application domain and improve classification performances. Since multi-kernel classification machine with reduced complexity, i.e., NMKMHKS, has a high performance to reduce both the time and space complexities of multiple kernel learning (MKL), so we introduce Universum learning into NMKMHKS and propose a Universum-based NMKMHKS (Uni-NMKMHKS). 56 pp. Englisch.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

      • Softcover
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      Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

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      Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

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      Seller: moluna, Greven, Germanymoluna

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      Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zhu ChangmingChangming Zhu received the B.S degree and PHD degree in Department of Computer Science and Engineering, East China University of Science and Technology (ECUST), China, 2010 and 2015 respectively. Currently he is a teache.

    • Language: English

      Published by LAP LAMBERT Academic Publishing Mär 2017, 2017

      3659707937 / 9783659707933

      • Softcover
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      Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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      Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Universum learning can reflect priori knowledge about application domain and improve classification performances. Since multi-kernel classification machine with reduced complexity, i.e., NMKMHKS, has a high performance to reduce both the time and space complexities of multiple kernel learning (MKL), so we introduce Universum learning into NMKMHKS and propose a Universum-based NMKMHKS (Uni-NMKMHKS).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2017

      3659707937 / 9783659707933

      • Softcover
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      Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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      Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Universum learning can reflect priori knowledge about application domain and improve classification performances. Since multi-kernel classification machine with reduced complexity, i.e., NMKMHKS, has a high performance to reduce both the time and space complexities of multiple kernel learning (MKL), so we introduce Universum learning into NMKMHKS and propose a Universum-based NMKMHKS (Uni-NMKMHKS).