FMINLBFGS: Fast Limited Memory Optimizer 1.0

FMINLBFGS is a Memory efficient optimizer for problems such as image registration with large amounts of unknowns, and cpu-expensive gradients.Supported:- Quasi Newton Broydend-deOCtFletcherd-deOCtGoldfarbd-deOCtShanno (BFGS).- Limited memory BFGS (L-BFGS).- Steepest Gradient Descent optimization.Advantages:- Quasi-Newton thus no need to provide a hessian, instead the hessian is updated by analyzing successive gradient vectors instead.- L-BFGS never explicitly forms or stores the Hessian matrix, which can be quite expensive when the number of dimensions becomes large.- There is an input option to replace gradient calls during linesearch with normal function calls, if the gradient is cpu-expensive.This function uses the same interface and options as Matlab functions such as fminunc and fminsearch. But optimset can be replaced by a simple struct when optimization toolbox not available.Example:options = optimset('GradObj', 'on' ,'Display', 'iter', 'HessUpdate', 'bfgs', 'GoalsExactAchieve',1);[x,fval] = fminlbfgs(@myfun, [1 1 1 1 1], options);

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Amounts,  Analyzing Successive,  Availableexampleoptions,  Be Quite,  Cpuexpensive,  Display,  Fminlbfgsmyfun,  Fminsearch,  Fminunc,  Goalsexactachieve Xfval,  Hessupdate Bfgs,  Image,  Input,  Iter Hessupdate,  Matlab,  Optimset Gradobj,  Options,  Replace Gra,  Replaced
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