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    ICML
    1999
    IEEE
    168views Machine Learning» more  ICML 1999»
    Least-Squares Temporal Difference Learning
    16 years 8 months ago
    Least-Squares Temporal Difference Learning
    Download  www.research.rutgers.edu
    Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
    Justin A. Boyan
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    KDD
    2009
    ACM
    192views Data Mining» more  KDD 2009»
    Learning optimal ranking with tensor factorization for tag recommendation
    16 years 8 months ago
    Learning optimal ranking with tensor factorization for tag recommendation
    Download  www.ismll.uni-hildesheim.de
    Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
    Steffen Rendle, Leandro Balby Marinho, Alexandros ...
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    KDD
    2009
    ACM
    132views Data Mining» more  KDD 2009»
    Learning patterns in the dynamics of biological networks
    16 years 8 months ago
    Learning patterns in the dynamics of biological networks
    Download  www-ai.cs.uni-dortmund.de
    Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
    Chang Hun You, Lawrence B. Holder, Diane J. Cook
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    KDD
    2008
    ACM
    159views Data Mining» more  KDD 2008»
    Semi-supervised learning with data calibration for long-term time series forecasting
    16 years 8 months ago
    Semi-supervised learning with data calibration for long-term time series forecasting
    Download  www.cse.msu.edu
    Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
    Haibin Cheng, Pang-Ning Tan
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    ICDM
    2009
    IEEE
    233views Data Mining» more  ICDM 2009»
    Semi-Supervised Sequence Labeling with Self-Learned Features
    16 years 2 months ago
    Semi-Supervised Sequence Labeling with Self-Learned Features
    Download  www.cs.cmu.edu
    —Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
    Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
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