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    TIP
    2010
    164views more  TIP 2010»
    A Marked Point Process for Modeling Lidar Waveforms
    13 years 2 months ago
    A Marked Point Process for Modeling Lidar Waveforms
    Download  recherche.ign.fr
    Lidar waveforms are 1D signals representing a train of echoes caused by reflections at different targets. Modeling these echoes with the appropriate parametric function is useful ...
    Clément Mallet, Florent Lafarge, Michel Rou...
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    ACL
    2009
    195views Computational Linguistics» more  ACL 2009»
    Distant supervision for relation extraction without labeled data
    13 years 5 months ago
    Distant supervision for relation extraction without labeled data
    Download  www.stanford.edu
    Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
    Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
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    SDM
    2009
    SIAM
    129views Data Mining» more  SDM 2009»
    Multi-topic Based Query-Oriented Summarization.
    14 years 5 months ago
    Multi-topic Based Query-Oriented Summarization.
    Download  www.siam.org
    Query-oriented summarization aims at extracting an informative summary from a document collection for a given query. It is very useful to help users grasp the main information rel...
    Dewei Chen, Jie Tang, Limin Yao
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    SIGIR
    2009
    ACM
    179views Information Technology» more  SIGIR 2009»
    Fast nonparametric matrix factorization for large-scale collaborative filtering
    14 years 2 months ago
    Fast nonparametric matrix factorization for large-scale collaborative filtering
    Download  www.cs.cmu.edu
    With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
    Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
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    TIP
    2010
    182views more  TIP 2010»
    Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
    13 years 2 months ago
    Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
    Download  c2inet.sce.ntu.edu.sg
    We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
    Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
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