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» Complex Matrix Decomposition and Quadratic Programming
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MOR
2007
116views more  MOR 2007»
13 years 4 months ago
Complex Matrix Decomposition and Quadratic Programming
This paper studies the possibilities of the Linear Matrix Inequality (LMI) characterization of the matrix cones formed by nonnegative complex Hermitian quadratic functions over sp...
Yongwei Huang, Shuzhong Zhang
ICRA
2010
IEEE
107views Robotics» more  ICRA 2010»
13 years 3 months ago
Fast resolution of hierarchized inverse kinematics with inequality constraints
— Classically, the inverse kinematics is performed by computing the singular value decomposition of the matrix to invert. This enables a very simple writing of the algorithm. How...
Adrien Escande, Nicolas Mansard, Pierre-Brice Wieb...
TSP
2010
12 years 11 months ago
Optimal linear fusion for distributed detection via semidefinite programming
Consider the problem of signal detection via multiple distributed noisy sensors. We propose a linear decision fusion rule to combine the local statistics from individual sensors i...
Zhi Quan, Wing-Kin Ma, Shuguang Cui, Ali H. Sayed
FOCS
2005
IEEE
13 years 10 months ago
On Non-Approximability for Quadratic Programs
This paper studies the computational complexity of the following type of quadratic programs: given an arbitrary matrix whose diagonal elements are zero, find x ∈ {−1, +1}n th...
Sanjeev Arora, Eli Berger, Elad Hazan, Guy Kindler...
JMLR
2006
89views more  JMLR 2006»
13 years 4 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel