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    SDM
    2007
    SIAM
    81views Data Mining» more  SDM 2007»
    A PAC Bound for Approximate Support Vector Machines
    13 years 10 months ago
    A PAC Bound for Approximate Support Vector Machines
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    We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
    Dongwei Cao, Daniel Boley
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    SDM
    2007
    SIAM
    149views Data Mining» more  SDM 2007»
    WAT: Finding Top-K Discords in Time Series Database
    13 years 10 months ago
    WAT: Finding Top-K Discords in Time Series Database
    Download  www.cse.cuhk.edu.hk
    Finding discords in time series database is an important problem in a great variety of applications, such as space shuttle telemetry, mechanical industry, biomedicine, and financ...
    Yingyi Bu, Oscar Tat-Wing Leung, Ada Wai-Chee Fu, ...
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    SDM
    2007
    SIAM
    130views Data Mining» more  SDM 2007»
    Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets
    13 years 10 months ago
    Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets
    Download  siam.org
    Decision lists (or ordered rule sets) have two attractive properties compared to unordered rule sets: they require a simpler classification procedure and they allow for a more co...
    Henrik Boström
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    SDM
    2007
    SIAM
    198views Data Mining» more  SDM 2007»
    Learning from Time-Changing Data with Adaptive Windowing
    13 years 10 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 10 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 10 months ago
    Multi-way Clustering on Relation Graphs
    Download  www-users.cs.umn.edu
    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 10 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 10 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 10 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 10 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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