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    LREC
    2008
    139views Education» more  LREC 2008»
    Identification of Comparable Argument-Head Relations in Parallel Corpora
    15 years 5 months ago
    Identification of Comparable Argument-Head Relations in Parallel Corpora
    Download  www.ling.uni-potsdam.de
    We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
    Kathrin Spreyer, Jonas Kuhn, Bettina Schrader
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    154
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    IM
    2007
    160views Computer Networks» more  IM 2007»
    Estimating End-to-End Performance by Collaborative Prediction with Active Sampling
    15 years 5 months ago
    Estimating End-to-End Performance by Collaborative Prediction with Active Sampling
    Download  domino.research.ibm.com
    — Accurately estimating end-to-end performance in distributed systems is essential both for monitoring compliance with service-level agreements (SLAs) and for performance optimiz...
    Irina Rish, Gerald Tesauro
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    IMAMS
    2007
    245views Mathematics» more  IMAMS 2007»
    Discrete Surface Ricci Flow: Theory and Applications
    15 years 5 months ago
    Discrete Surface Ricci Flow: Theory and Applications
    Download  www.cs.sunysb.edu
    Conformal geometry is in the core of pure mathematics. Conformal structure is more flexible than Riemaniann metric but more rigid than topology. Conformal geometric methods have p...
    Miao Jin, Junho Kim, Xianfeng David Gu
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    114
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    SDM
    2007
    SIAM
    104views Data Mining» more  SDM 2007»
    Boosting Optimal Logical Patterns Using Noisy Data
    15 years 5 months ago
    Boosting Optimal Logical Patterns Using Noisy Data
    Download  siam.org
    We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
    Noam Goldberg, Chung-chieh Shan
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    138
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    SDM
    2007
    SIAM
    143views Data Mining» more  SDM 2007»
    Less is More: Compact Matrix Decomposition for Large Sparse Graphs
    15 years 5 months ago
    Less is More: Compact Matrix Decomposition for Large Sparse Graphs
    Download  www.cs.cmu.edu
    Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
    Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
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