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    AI
    1998
    Springer
    103views Artificial Intelligence» more  AI 1998»
    Worst-Case Analysis of the Perceptron and Exponentiated Update Algorithms
    13 years 7 months ago
    Worst-Case Analysis of the Perceptron and Exponentiated Update Algorithms
    Download  www.cs.utsa.edu
    The absolute loss is the absolute difference between the desired and predicted outcome. This paper demonstrates worst-case upper bounds on the absolute loss for the Perceptron le...
    Tom Bylander
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    KDD
    2007
    ACM
    197views Data Mining» more  KDD 2007»
    Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
    14 years 8 months ago
    Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
    Download  www.public.asu.edu
    The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
    Jieping Ye, Shuiwang Ji, Jianhui Chen
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    JMLR
    2008
    151views more  JMLR 2008»
    Learning to Combine Motor Primitives Via Greedy Additive Regression
    13 years 7 months ago
    Learning to Combine Motor Primitives Via Greedy Additive Regression
    Download  www.bcs.rochester.edu
    The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
    Manu Chhabra, Robert A. Jacobs
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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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    KDD
    2010
    ACM
    245views Data Mining» more  KDD 2010»
    Learning incoherent sparse and low-rank patterns from multiple tasks
    13 years 9 months ago
    Learning incoherent sparse and low-rank patterns from multiple tasks
    Download  www.public.asu.edu
    We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
    Jianhui Chen, Ji Liu, Jieping Ye
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