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    CIVR
    2005
    Springer
    123views Image Analysis» more  CIVR 2005»
    Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
    14 years 3 months ago
    Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
    Download  sci2s.ugr.es
    Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
    Chengcui Zhang, Xin Chen
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    NIPS
    1998
    154views Information Technology» more  NIPS 1998»
    Semi-Supervised Support Vector Machines
    13 years 11 months ago
    Semi-Supervised Support Vector Machines
    Download  www1.cs.columbia.edu
    We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
    Kristin P. Bennett, Ayhan Demiriz
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    ICMLA
    2010
    229views Machine Learning» more  ICMLA 2010»
    Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
    13 years 8 months ago
    Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
    Download  www.seas.upenn.edu
    Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
    Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
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    JMLR
    2006
    140views more  JMLR 2006»
    Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
    13 years 10 months ago
    Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
    Download  jmlr.csail.mit.edu
    The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
    Masashi Sugiyama
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    WILF
    2005
    Springer
    194views Fuzzy Logic» more  WILF 2005»
    Learning Bayesian Classifiers from Gene-Expression MicroArray Data
    14 years 3 months ago
    Learning Bayesian Classifiers from Gene-Expression MicroArray Data
    Download  www.mi.ieiit.cnr.it
    Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
    Andrea Bosin, Nicoletta Dessì, Diego Libera...
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