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Approximate Invariant Subspaces and QuasiNewton Optimization Methods
, 2009
"... New approximate secant equations are shown to result from the knowledge of (problem dependent) invariant subspace information, which in turn suggests improvements in quasiNewton methods for unconstrained minimization. A new limitedmemory BFGS using approximate secant equations is then derived and i ..."
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New approximate secant equations are shown to result from the knowledge of (problem dependent) invariant subspace information, which in turn suggests improvements in quasiNewton methods for unconstrained minimization. A new limitedmemory BFGS using approximate secant equations is then derived
On the realization of the Wolfe conditions in reduced quasiNewton methods for equality constrained optimization
 SIAM Journal on Optimization
, 1997
"... Abstract. This paper describes a reduced quasiNewton method for solving equality constrained optimization problems. A major difficulty encountered by this type of algorithm is the design of a consistent technique for maintaining the positive definiteness of the matrices approximating the reduced He ..."
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Cited by 6 (0 self)
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Abstract. This paper describes a reduced quasiNewton method for solving equality constrained optimization problems. A major difficulty encountered by this type of algorithm is the design of a consistent technique for maintaining the positive definiteness of the matrices approximating the reduced
ReducedHessian QuasiNewton Methods For Unconstrained Optimization
 SIAM J. OPTIM
, 1999
"... QuasiNewton methods are reliable and efficient on a wide range of problems, but they can require many iterations if the problem is illconditioned or if a poor initial estimate of the Hessian is used. In this paper, we discuss methods designed to be more efficient in these situations. All the metho ..."
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Cited by 9 (1 self)
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QuasiNewton methods are reliable and efficient on a wide range of problems, but they can require many iterations if the problem is illconditioned or if a poor initial estimate of the Hessian is used. In this paper, we discuss methods designed to be more efficient in these situations. All
A Survey of Multistep QuasiNewton Methods
 Proceedings of the International Conference on Scientific Computations, Beirut
, 1999
"... QuasiNewton methods have been utilized as a standard technique for solving nonlinear optimization problems and nonlinear systems of equations for over thirty years. These methods, in almost all cases, make use of data obtained from the step just completed in the variable space to revise the current ..."
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Cited by 1 (0 self)
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QuasiNewton methods have been utilized as a standard technique for solving nonlinear optimization problems and nonlinear systems of equations for over thirty years. These methods, in almost all cases, make use of data obtained from the step just completed in the variable space to revise
QUASINEWTON MODIFICATIONS TO SNOPT
"... minimize x∈Rn f(x) subject to c(x) ≥ 0, where f: Rn → R and c: Rn → Rm are twice continuously differentiable functions. Let g(x) denote the gradient of f(x), and J(x) the mxn Jacobian matrix of c(x), with rows the gradients of c(x). A point x ∗ is feasible with respect to the constraints c(x) if c ..."
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in the neighborhood. If the inequality is strict for all feasible x 6 = x∗, then x ∗ is a strong local minimizer. Otherwise, x ∗ is a weak local minimizer. Nonlinearly constrained problems have an abundance of diverse applications in engineering, finance, trajectory optimization, and many additional fields
SelfScaling Parallel QuasiNewton Methods
"... In this paper, a new class of selfscaling quasiNewton#SSQN# updates for solving unconstrained nonlinear optimization problems#UNOPs# is proposed. It is shown that many existing QN updates can be considered as special cases of the new family.Parallel SSQN algorithms based on this class of class of ..."
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In this paper, a new class of selfscaling quasiNewton#SSQN# updates for solving unconstrained nonlinear optimization problems#UNOPs# is proposed. It is shown that many existing QN updates can be considered as special cases of the new family.Parallel SSQN algorithms based on this class of class
Insertion sequences
 Microbiol Mol. Biol. Rev
, 1998
"... These include: Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» Downloaded from ..."
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Cited by 426 (3 self)
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These include: Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» Downloaded from
AN ONLINE QUASINEWTON ALGORITHM FOR BLIND SIMO IDENTIFICATION
"... In the last decade various time and frequencydomain algorithms were derived to blindly identify acoustic systems. One of these algorithms is the multichannel Newton (MCN) algorithm, which is also the basis of the well known normalized multichannel frequencydomain leastmeansquare (NMCFLMS) alg ..."
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that updates the inverse of the Hessian by analyzing successive gradient vectors. The new MCQN is shown to exhibit similar performance to MCN but with much reduced complexity. Index Terms — blind system identification, Newton method, quasiNewton method, multichannel signal processing. 1.
Newton and QuasiNewton Methods for Normal Maps with Polyhedral Sets1
"... Abstract. We present a generalized Newton method and a quasiNewton method for solving H(x): = F(nc(x))+xnc(x) = 0, when C is a polyhedral set. For both the Newton and quasiNewton methods considered here, the subproblem to be solved is a linear system of equations per iteration. The other charac ..."
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Abstract. We present a generalized Newton method and a quasiNewton method for solving H(x): = F(nc(x))+xnc(x) = 0, when C is a polyhedral set. For both the Newton and quasiNewton methods considered here, the subproblem to be solved is a linear system of equations per iteration. The other
FlowMap: An Optimal Technology Mapping Algorithm for Delay Optimization in LookupTable Based FPGA Designs
 IEEE TRANS. CAD
, 1994
"... The field programmable gatearray (FPGA) has become an important technology in VLSI ASIC designs. In the past a few years, a number of heuristic algorithms have been proposed for technology mapping in lookuptable (LUT) based FPGA designs, but none of them guarantees optimal solutions for general Bo ..."
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Cited by 317 (41 self)
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The field programmable gatearray (FPGA) has become an important technology in VLSI ASIC designs. In the past a few years, a number of heuristic algorithms have been proposed for technology mapping in lookuptable (LUT) based FPGA designs, but none of them guarantees optimal solutions for general
Results 1  10
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493,959