Multiple instance learning

Results: 43



#Item
1Journal of Machine Learning Research–816  Submitted 11/03; Revised 12/04; Published 5/05 Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application

Journal of Machine Learning Research–816 Submitted 11/03; Revised 12/04; Published 5/05 Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application

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Source URL: dsp.ucsd.edu

Language: English - Date: 2018-07-19 19:02:54
    2A Self-paced Multiple-instance Learning Framework for Co-saliency Detection Dingwen Zhang1, Deyu Meng2, Chao Li1, Lu Jiang3, Qian Zhao2, and Junwei Han1* 1 School of Automation, Northwestern Polytechnical University 2 Sc

    A Self-paced Multiple-instance Learning Framework for Co-saliency Detection Dingwen Zhang1, Deyu Meng2, Chao Li1, Lu Jiang3, Qian Zhao2, and Junwei Han1* 1 School of Automation, Northwestern Polytechnical University 2 Sc

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    Source URL: www.cv-foundation.org

    - Date: 2015-10-24 15:03:43
      3Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering Yan Xu∗1,2 , Jun-Yan Zhu∗2,3 , Eric Chang2 and Zhuowen Tu2,4 State Key Laboratory of Software Developme

      Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering Yan Xu∗1,2 , Jun-Yan Zhu∗2,3 , Eric Chang2 and Zhuowen Tu2,4 State Key Laboratory of Software Developme

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      Source URL: pages.ucsd.edu

      - Date: 2014-09-19 15:50:33
        4Many learning tasks, such as cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of learning data with the others. We introduc

        Many learning tasks, such as cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of learning data with the others. We introduc

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        Source URL: mmds-data.org

        - Date: 2016-06-23 15:50:48
          5Max-Margin Multiple-Instance Dictionary Learning  Xinggang Wang†  Baoyuan Wang‡

          Max-Margin Multiple-Instance Dictionary Learning Xinggang Wang† Baoyuan Wang‡

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          Source URL: pages.ucsd.edu

          Language: English - Date: 2013-06-24 00:00:30
          6A Conditional Random Field for Multiple-Instance Learning  Thomas Deselaers Vittorio Ferrari Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland

          A Conditional Random Field for Multiple-Instance Learning Thomas Deselaers Vittorio Ferrari Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland

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          Source URL: thomas.deselaers.de

          Language: English - Date: 2014-10-11 09:29:28
          7Harvesting Mid-level Visual Concepts from Large-scale Internet Images Quannan Li1 , Jiajun Wu2 , Zhuowen Tu1 1 Lab of Neuro Imaging and Department of Computer Science, UCLA 2 Institute for Interdisciplinary Information S

          Harvesting Mid-level Visual Concepts from Large-scale Internet Images Quannan Li1 , Jiajun Wu2 , Zhuowen Tu1 1 Lab of Neuro Imaging and Department of Computer Science, UCLA 2 Institute for Interdisciplinary Information S

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          Source URL: pages.ucsd.edu

          Language: English - Date: 2013-04-17 01:26:45
          8Semi-Supervised Learning with Adversarially Missing Label Information Umar Syed Ben Taskar Department of Computer and Information Science

          Semi-Supervised Learning with Adversarially Missing Label Information Umar Syed Ben Taskar Department of Computer and Information Science

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          Source URL: www.seas.upenn.edu

          Language: English - Date: 2010-11-04 10:51:45
          9Many learning tasks, such as cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of learning data with the others. We introduc

          Many learning tasks, such as cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of learning data with the others. We introduc

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          Source URL: mmds-data.org

          - Date: 2016-06-23 15:50:48
            10Contexts-Constrained Multiple Instance Learning for Histopathology Image Analysis Yan Xu1,2 , Jianwen Zhang2 , Eric I-Chao Chang2 , Maode Lai4 , and Zhuowen Tu2,3 1 State Key Laboratory of Software Development Environmen

            Contexts-Constrained Multiple Instance Learning for Histopathology Image Analysis Yan Xu1,2 , Jianwen Zhang2 , Eric I-Chao Chang2 , Maode Lai4 , and Zhuowen Tu2,3 1 State Key Laboratory of Software Development Environmen

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            Source URL: pages.ucsd.edu

            Language: English - Date: 2013-02-23 14:26:54