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    OL
    2007
    133views more  OL 2007»
    An SQP-type algorithm for nonlinear second-order cone programs
    13 years 6 months ago
    An SQP-type algorithm for nonlinear second-order cone programs
    Download  www.amp.i.kyoto-u.ac.jp
    We propose an SQP-type algorithm for solving nonlinear second-order cone programming (NSOCP) problems. At every iteration, the algorithm solves a convex SOCP subproblem in which th...
    Hirokazu Kato, Masao Fukushima
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    MP
    1998
    83views more  MP 1998»
    A modified layered-step interior-point algorithm for linear programming
    13 years 7 months ago
    A modified layered-step interior-point algorithm for linear programming
    Download  theory.stanford.edu
    The layered-step interior-point algorithm was introduced by Vavasis and Ye. The algorithm accelerates the path following interior-point algorithm and its arithmetic complexity dep...
    Nimrod Megiddo, Shinji Mizuno, Takashi Tsuchiya
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    JMLR
    2012
    176views Programming Languages» more  JMLR 2012»
    Fast interior-point inference in high-dimensional sparse, penalized state-space models
    11 years 9 months ago
    Fast interior-point inference in high-dimensional sparse, penalized state-space models
    Download  www.stat.columbia.edu
    We present an algorithm for fast posterior inference in penalized high-dimensional state-space models, suitable in the case where a few measurements are taken in each time step. W...
    Eftychios A. Pnevmatikakis, Liam Paninski
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    GECCO
    2007
    Springer
    209views Optimization» more  GECCO 2007»
    Kernel based automatic clustering using modified particle swarm optimization algorithm
    14 years 1 months ago
    Kernel based automatic clustering using modified particle swarm optimization algorithm
    Download  www.softcomputing.net
    This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
    Ajith Abraham, Swagatam Das, Amit Konar
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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 7 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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