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    ICML
    2009
    IEEE
    186views Machine Learning» more  ICML 2009»
    Regularization and feature selection in least-squares temporal difference learning
    14 years 8 months ago
    Regularization and feature selection in least-squares temporal difference learning
    Download  ai.stanford.edu
    We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
    J. Zico Kolter, Andrew Y. Ng
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    SADM
    2008
    178views more  SADM 2008»
    Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem
    13 years 7 months ago
    Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem
    Download  www.cs.utexas.edu
    : Nonnegative matrix approximation (NNMA) is a popular matrix decomposition technique that has proven to be useful across a diverse variety of fields with applications ranging from...
    Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
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    BIBE
    2007
    IEEE
    159views Bioinformatics» more  BIBE 2007»
    Non-negative Tensor Factorization Based on Alternating Large-scale Non-negativity-constrained Least Squares
    13 years 11 months ago
    Non-negative Tensor Factorization Based on Alternating Large-scale Non-negativity-constrained Least Squares
    Download  www.cc.gatech.edu
    Non-negative matrix factorization (NMF) and non-negative tensor factorization (NTF) have attracted much attention and have been successfully applied to numerous data analysis probl...
    Hyunsoo Kim, Haesun Park, Lars Eldén
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    JAIR
    2002
    163views more  JAIR 2002»
    Efficient Reinforcement Learning Using Recursive Least-Squares Methods
    13 years 7 months ago
    Efficient Reinforcement Learning Using Recursive Least-Squares Methods
    Download  www.jair.org
    The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
    Xin Xu, Hangen He, Dewen Hu
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    ICML
    2008
    IEEE
    155views Machine Learning» more  ICML 2008»
    A least squares formulation for canonical correlation analysis
    14 years 8 months ago
    A least squares formulation for canonical correlation analysis
    Download  www.public.asu.edu
    Canonical Correlation Analysis (CCA) is a well-known technique for finding the correlations between two sets of multi-dimensional variables. It projects both sets of variables int...
    Liang Sun, Shuiwang Ji, Jieping Ye
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