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SIAMJO
2008
212views more  SIAMJO 2008»
13 years 7 months ago
Convergence Rate of an Optimization Algorithm for Minimizing Quadratic Functions with Separable Convex Constraints
A new active set algorithm for minimizing quadratic functions with separable convex constraints is proposed by combining the conjugate gradient method with the projected gradient. ...
Radek Kucera
TSP
2010
13 years 2 months ago
A dual perspective on separable semidefinite programming with applications to optimal downlink beamforming
This paper considers the downlink beamforming optimization problem that minimizes the total transmission power subject to global shaping constraints and individual shaping constrai...
Yongwei Huang, Daniel Pérez Palomar
ICCAD
2005
IEEE
107views Hardware» more  ICCAD 2005»
14 years 4 months ago
Projection-based performance modeling for inter/intra-die variations
Large-scale process fluctuations in nano-scale IC technologies suggest applying high-order (e.g., quadratic) response surface models to capture the circuit performance variations....
Xin Li, Jiayong Le, Lawrence T. Pileggi, Andrzej J...
IFIP
2005
Springer
14 years 1 months ago
A New Low Rank Quasi-Newton Update Scheme for Nonlinear Programming
A new quasi-Newton scheme for updating a low rank positive semi-definite Hessian approximation is described, primarily for use in sequential quadratic programming methods for non...
R. Fletcher
TSP
2010
13 years 2 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