Feature vector

Results: 359



#Item
51Dynamic Texture Recognition via Orthogonal Tensor Dictionary Learning Yuhui Quan1 , Yan Huang2 , Hui Ji1 1 2

Dynamic Texture Recognition via Orthogonal Tensor Dictionary Learning Yuhui Quan1 , Yan Huang2 , Hui Ji1 1 2

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Source URL: www.cv-foundation.org

Language: English
52Deep Feature Synthesis: Towards Automating Data Science Endeavors James Max Kanter Kalyan Veeramachaneni

Deep Feature Synthesis: Towards Automating Data Science Endeavors James Max Kanter Kalyan Veeramachaneni

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Source URL: groups.csail.mit.edu

Language: English - Date: 2015-10-15 14:47:29
53Model selection Large scale model selection Summary and open problems Model Selection and Computational Oracle Inequalities for Large Scale Problems

Model selection Large scale model selection Summary and open problems Model Selection and Computational Oracle Inequalities for Large Scale Problems

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Source URL: www.stat.berkeley.edu

Language: English - Date: 2012-07-10 18:14:07
54Feature Clustering for Accelerating Parallel Coordinate Descent Chad Scherrer Independent Consultant Yakima, WA

Feature Clustering for Accelerating Parallel Coordinate Descent Chad Scherrer Independent Consultant Yakima, WA

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Source URL: dept.stat.lsa.umich.edu

Language: English - Date: 2013-01-18 21:24:37
55JMLR: Workshop and Conference Proceedings 1: 1-16  KDD Cup 2010 Feature Engineering and Classifier Ensemble for KDD Cup 2010

JMLR: Workshop and Conference Proceedings 1: 1-16 KDD Cup 2010 Feature Engineering and Classifier Ensemble for KDD Cup 2010

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Source URL: pslcdatashop.org

Language: English - Date: 2012-10-29 14:34:19
56Parallel Feature Selection inspired by Group Testing Yingbo Zhou∗ Utkarsh Porwal∗ CSE Department SUNY at Buffalo {yingbozh, utkarshp}@buffalo.edu

Parallel Feature Selection inspired by Group Testing Yingbo Zhou∗ Utkarsh Porwal∗ CSE Department SUNY at Buffalo {yingbozh, utkarshp}@buffalo.edu

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Source URL: papers.nips.cc

Language: English - Date: 2014-12-02 18:42:35
57Going Mini: Extreme Lightweight Spam Filters D. Sculley Gordon V. Cormack  Google, Inc.

Going Mini: Extreme Lightweight Spam Filters D. Sculley Gordon V. Cormack Google, Inc.

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Source URL: plg.uwaterloo.ca

Language: English - Date: 2009-05-28 18:47:16
58A Survey of Binary Similarity and Distance Measures Seung-Seok Choi, Sung-Hyuk Cha, Charles C. Tappert Department of Computer Science, Pace University New York, US ABSTRACT The binary feature vector is one of the most co

A Survey of Binary Similarity and Distance Measures Seung-Seok Choi, Sung-Hyuk Cha, Charles C. Tappert Department of Computer Science, Pace University New York, US ABSTRACT The binary feature vector is one of the most co

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Source URL: www.iiisci.org

Language: English - Date: 2013-09-13 20:30:47
    59DISTINCTIVE FEATURE DETECTION USING SUPPORT VECTOR MACHINES Partha Niyogi, Chris Burges, and Padma Ramesh Bell Labs, Lucent Technologies, USA. ABSTRACT  dcl d

    DISTINCTIVE FEATURE DETECTION USING SUPPORT VECTOR MACHINES Partha Niyogi, Chris Burges, and Padma Ramesh Bell Labs, Lucent Technologies, USA. ABSTRACT dcl d

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    Source URL: people.cs.uchicago.edu

    Language: English - Date: 2006-06-02 15:10:44
      60Materialization Optimizations for Feature Selection Workloads Ce Zhang†‡ †  Arun Kumar†

      Materialization Optimizations for Feature Selection Workloads Ce Zhang†‡ † Arun Kumar†

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      Source URL: cs.stanford.edu

      Language: English - Date: 2014-03-30 16:39:39