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    UAI
    2004
    189views Artificial Intelligence» more  UAI 2004»
    A Bayesian Approach toward Active Learning for Collaborative Filtering
    13 years 9 months ago
    A Bayesian Approach toward Active Learning for Collaborative Filtering
    Download  www.cs.cmu.edu
    Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the perfo...
    Rong Jin, Luo Si
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    AAAI
    2008
    155views Intelligent Agents» more  AAAI 2008»
    Active Learning for Pipeline Models
    13 years 10 months ago
    Active Learning for Pipeline Models
    Download  www.aaai.org
    For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
    Dan Roth, Kevin Small
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    NIPS
    2007
    188views Information Technology» more  NIPS 2007»
    Discriminative Batch Mode Active Learning
    13 years 9 months ago
    Discriminative Batch Mode Active Learning
    Download  www.cis.temple.edu
    Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning...
    Yuhong Guo, Dale Schuurmans
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    CEC
    2007
    IEEE
    128views Artificial Intelligence» more  CEC 2007»
    A study on the design issues of Memetic Algorithm
    14 years 2 months ago
    A study on the design issues of Memetic Algorithm
    Download  ntu-cg.ntu.edu.sg
    — Over the recent years, there has been increasing research activities made on improving the efficacy of Memetic Algorithm (MA) for solving complex optimization problems. Partic...
    Q. H. Nguyen, Yew-Soon Ong, Natalio Krasnogor
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    SDM
    2010
    SIAM
    156views Data Mining» more  SDM 2010»
    Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
    13 years 9 months ago
    Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
    Download  cs.ucla.edu
    We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
    Alireza Vahdatpour, Majid Sarrafzadeh
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