Hessian

For a symbolic input function f, returns the symbolic Hessian matrix. A real time saver imho I don't know how useful anyone will find this, but eh, my professor made us do it on the test, so I figure this will save at least someone the headache of having to find the Hessian by hand (provided they... Platforms: Matlab

The Hessian binary web service protocol makes web services usable without requiring a large framework, and without learning yet another alphabet soup of protocols. Because it is a binary protocol, it is well-suited to sending binary data without any need to extend the protocol with attachments.... Platforms: Windows, Mac, *nix, Flash, BSD Solaris

"The Hessian binary web service protocol makes web services usable without requiring a large framework, and without learning yet another alphabet soup of protocols. Because it is a binary protocol, it is well-suited to sending binary data without any need to extend the protocol with attachments."... Platforms: BSD

hessiancpp is a C++ library implementing the client side of the Caucho Hessian protocol.Aside from basic protocol implementation is also supports GZipped replies, a feature that can greatly decrease the message size on the wire. Platforms: *nix

OpenDiscreteDynamicProgrammingTemplate project founds optimal constrainted parameters of a discrete controls with second order optimization template replacing Hessian with directional derivatives and backpropagation for digital filter(as neural network).. OpenDiscreteDynamicProgrammingTemplate:... Platforms: *nix

L-BFGS-B is a collection of Fortran 77 routines for solving nonlinear optimization problems with bound constraints on the variables. One of the key features of the nonlinear solver is that the Hessian is not needed. I've designed an interface to the L-BFGS-B solver so that it can be called like... Platforms: Matlab

This script is capable of solving a convex quadratic programming problem by Wolf's method. For the convergence of the algorithm it is necessary that either Hessian of the objective function be positive definite or positive semidefinite Hessian with linear term zero. For theory of Wolf method and... Platforms: Matlab

This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others (see references for more... Platforms: Matlab

This script may be easily converted to a function which could be an extremely useful subroutine in optimization problems to check whether the objective function is globally convex. It may also be used to derive the expressions for gradient and Hessian of the given multidimensional real valued... Platforms: Matlab

The RSQP Toolbox is developed based on the theory of reduced Hessian successive quadratic programming for large scale optimization.The toolbox is a collection of functions that extend the capability of MATLAB Optimization Toolbox in solving optimization problems with(a)high dimensionality... Platforms: Matlab

Mustaine is a Python implemention of the Hessian 1.0.2 specification, a binary web services protocol. The library currently provides a standard HTTP-based client as well as a general-purpose serialization library. Server support is planned. Using mustaine.client Testing against Caucho's... Platforms: *nix

Crispy is a client for remote invocation for different kinds of services via proxies. The intention for this project is a very simple API for call different kinds of services (provider/technology). Crispys aims is to provide a single point of entry for remote invocation for a wide number of... Platforms: *nix

HessianKit is a Framework for Objective-C 2.0 to allow applications for Mac OS X 10.5, and iPhone 2.0 or later to communicate with Hessian web services. The main goals; Be compliant and forgiving, seamless Objective-C experience, and avoid glue-code. Platforms: Mac

The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex... Platforms: Windows, Mac, Linux

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... Platforms: Matlab

Replace your function in the code and the output will be similar to the followingSteepest Descent Method=============Function = -(3*x1+x2+6*x1*x2-2*(x1^2)+2*(x2^2))Hessian...... [ 4 -6] [ ] [-6 -4]Gradient...... [-3 - 6 x2 + 4 x1] [ ] [-1 - 6 x1 - 4 x2]Eigen Values[ 2*13^(1/2), 0][ 0,... Platforms: Matlab

Ok, yes, my expectation was that when I saw this, before I downloaded it I expected it to be a student's homework assigment. In fact, this is a reasonably carefully crafted tool.One serious issue is that this code requires you to provide explicit functional forms for the gradient and Hessian.... Platforms: Matlab