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    KDD
    2009
    ACM
    170views Data Mining» more  KDD 2009»
    Picture this: preferences for image search
    13 years 11 months ago
    Picture this: preferences for image search
    Download  research.microsoft.com
    Paul N. Bennett, David Maxwell Chickering, Anton M...
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    KDD
    2009
    ACM
    168views Data Mining» more  KDD 2009»
    CAPTCHA-based image labeling on the Soylent Grid
    13 years 11 months ago
    CAPTCHA-based image labeling on the Soylent Grid
    Download  vision.ucsd.edu
    We introduce an open labeling platform for Computer Vision researchers based on Captchas, creating as a byproduct labeled image data sets while supporting web security. For the tw...
    Peter Faymonville, Kai Wang, John Miller, Serge J....
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    KDD
    2009
    ACM
    174views Data Mining» more  KDD 2009»
    Learning from data with uncertain labels by boosting credal classifiers
    13 years 11 months ago
    Learning from data with uncertain labels by boosting credal classifiers
    Download  www.hds.utc.fr
    Benjamin Quost, Thierry Denoeux
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    KDD
    2009
    ACM
    179views Data Mining» more  KDD 2009»
    Identifying graphs from noisy and incomplete data
    13 years 11 months ago
    Identifying graphs from noisy and incomplete data
    Download  waimea.cs.umd.edu
    There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
    Galileo Mark S. Namata Jr., Lise Getoor
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    KDD
    2009
    ACM
    205views Data Mining» more  KDD 2009»
    From active towards InterActive learning: using consideration information to improve labeling correctness
    13 years 11 months ago
    From active towards InterActive learning: using consideration information to improve labeling correctness
    Download  www.ifi.uzh.ch
    Data mining techniques have become central to many applications. Most of those applications rely on so called supervised learning algorithms, which learn from given examples in th...
    Abraham Bernstein, Jiwen Li
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    KDD
    2009
    ACM
    298views Data Mining» more  KDD 2009»
    Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
    13 years 11 months ago
    Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
    Download  www-ai.cs.uni-dortmund.de
    One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, ...
    Rong Pan, Martin Scholz
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    KDD
    2009
    ACM
    167views Data Mining» more  KDD 2009»
    Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
    13 years 11 months ago
    Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
    Download  www.comp.nus.edu.sg
    Anomalous windows are the contiguous groupings of data points. In this paper, we propose an approach for discovering anomalous windows using Scan Statistics for Linear Intersectin...
    Lei Shi, Vandana Pursnani Janeja
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    KDD
    2009
    ACM
    129views Data Mining» more  KDD 2009»
    Spatial-temporal causal modeling for climate change attribution
    13 years 11 months ago
    Spatial-temporal causal modeling for climate change attribution
    Download  www.niculescu-mizil.org
    Aurelie C. Lozano, Hongfei Li, Alexandru Niculescu...
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    KDD
    2009
    ACM
    192views Data Mining» more  KDD 2009»
    Primal sparse Max-margin Markov networks
    13 years 11 months ago
    Primal sparse Max-margin Markov networks
    Download  www.cs.cmu.edu
    Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
    Jun Zhu, Eric P. Xing, Bo Zhang
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    KDD
    2009
    ACM
    655views Data Mining» more  KDD 2009»
    Regression-based latent factor models
    13 years 11 months ago
    Regression-based latent factor models
    Download  www-ai.cs.uni-dortmund.de
    Deepak Agarwal, Bee-Chung Chen
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