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    SDM
    2007
    SIAM
    198views Data Mining» more  SDM 2007»
    Learning from Time-Changing Data with Adaptive Windowing
    13 years 6 months ago
    Learning from Time-Changing Data with Adaptive Windowing
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    We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
    Albert Bifet, Ricard Gavaldà
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    SDM
    2007
    SIAM
    137views Data Mining» more  SDM 2007»
    Are approximation algorithms for consensus clustering worthwhile?
    13 years 6 months ago
    Are approximation algorithms for consensus clustering worthwhile?
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    Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated...
    Michael Bertolacci, Anthony Wirth
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    SDM
    2007
    SIAM
    177views Data Mining» more  SDM 2007»
    Multi-way Clustering on Relation Graphs
    13 years 6 months ago
    Multi-way Clustering on Relation Graphs
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    A number of real-world domains such as social networks and e-commerce involve heterogeneous data that describes relations between multiple classes of entities. Understanding the n...
    Arindam Banerjee, Sugato Basu, Srujana Merugu
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    SDM
    2007
    SIAM
    187views Data Mining» more  SDM 2007»
    Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
    13 years 6 months ago
    Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
    Download  www-users.cs.umn.edu
    Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
    Arindam Banerjee, Sugato Basu
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    SDM
    2007
    SIAM
    120views Data Mining» more  SDM 2007»
    An Analysis of Logistic Models: Exponential Family Connections and Online Performance
    13 years 6 months ago
    An Analysis of Logistic Models: Exponential Family Connections and Online Performance
    Download  www-users.cs.umn.edu
    Logistic models are arguably one of the most widely used data analysis techniques. In this paper, we present analyses focussing on two important aspects of logistic models—its r...
    Arindam Banerjee
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    SDM
    2007
    SIAM
    131views Data Mining» more  SDM 2007»
    Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
    13 years 6 months ago
    Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
    Download  www.cs.ucla.edu
    In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
    Yijian Bai, Haixun Wang, Carlo Zaniolo
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    SDM
    2007
    SIAM
    162views Data Mining» more  SDM 2007»
    Probabilistic Joint Feature Selection for Multi-task Learning
    13 years 6 months ago
    Probabilistic Joint Feature Selection for Multi-task Learning
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    We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
    Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
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    SDM
    2007
    SIAM
    195views Data Mining» more  SDM 2007»
    On Anonymization of String Data
    13 years 6 months ago
    On Anonymization of String Data
    Download  www.charuaggarwal.net
    String data is especially important in the privacy preserving data mining domain because most DNA and biological data is coded as strings. In this paper, we will discuss a new met...
    Charu C. Aggarwal, Philip S. Yu
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    SDM
    2007
    SIAM
    118views Data Mining» more  SDM 2007»
    On Privacy-Preservation of Text and Sparse Binary Data with Sketches
    13 years 6 months ago
    On Privacy-Preservation of Text and Sparse Binary Data with Sketches
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    In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high...
    Charu C. Aggarwal, Philip S. Yu
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    SDM
    2007
    SIAM
    133views Data Mining» more  SDM 2007»
    On Point Sampling Versus Space Sampling for Dimensionality Reduction
    13 years 6 months ago
    On Point Sampling Versus Space Sampling for Dimensionality Reduction
    Download  www.charuaggarwal.net
    In recent years, random projection has been used as a valuable tool for performing dimensionality reduction of high dimensional data. Starting with the seminal work of Johnson and...
    Charu C. Aggarwal
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