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    AAAI
    2006
    229views Intelligent Agents» more  AAAI 2006»
    When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions
    13 years 10 months ago
    When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions
    Download  www.bkveton.com
    Intrusion attempts due to self-propagating code are becoming an increasingly urgent problem, in part due to the homogeneous makeup of the internet. Recent advances in anomalybased...
    Denver Dash, Branislav Kveton, John Mark Agosta, E...
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    CHI
    2007
    ACM
    171views Human Computer Interaction» more  CHI 2007»
    Modeling pointing at targets of arbitrary shapes
    14 years 9 months ago
    Modeling pointing at targets of arbitrary shapes
    Download  www.cs.berkeley.edu
    We investigate pointing at graphical targets of arbitrary shapes. We first describe a previously proposed probabilistic Fitts' law model [7] which, unlike previous models tha...
    Tovi Grossman, Nicholas Kong, Ravin Balakrishnan
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    ICML
    2003
    IEEE
    129views Machine Learning» more  ICML 2003»
    Learning on the Test Data: Leveraging Unseen Features
    14 years 9 months ago
    Learning on the Test Data: Leveraging Unseen Features
    Download  www.cis.upenn.edu
    This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
    Benjamin Taskar, Ming Fai Wong, Daphne Koller
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    JMLR
    2010
    117views more  JMLR 2010»
    Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
    13 years 3 months ago
    Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
    Download  jmlr.csail.mit.edu
    Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
    Xinhua Zhang, Thore Graepel, Ralf Herbrich
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    NIPS
    2008
    159views Information Technology» more  NIPS 2008»
    Structured ranking learning using cumulative distribution networks
    13 years 10 months ago
    Structured ranking learning using cumulative distribution networks
    Download  research.microsoft.com
    Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
    Jim C. Huang, Brendan J. Frey
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