Dear professor Michael Creel, if we have an optimization problem and we remark that most of the time the hessian matrix is not invertible and when this applies to the outer product of gradient, is it possible in this case to use the in-built function "pinv" to calculate the pseudo inverse for the Hessian or the outer product of matrix? Can you please give me a reference that outlines the utility of scaling the data to facilitate convergence in an optimization problem. Let me put this reference in my thesis's bibliography. Many thanks in advance and best regards, George. -- View this message in context: http://old.nabble.com/about-the-inversion-of-the-hessian-tp27384931p27384931.html Sent from the octave-dev mailing list archive at Nabble.com.
------------------------------------------------------------------------------ The Planet: dedicated and managed hosting, cloud storage, colocation Stay online with enterprise data centers and the best network in the business Choose flexible plans and management services without long-term contracts Personal 24x7 support from experience hosting pros just a phone call away. http://p.sf.net/sfu/theplanet-com _______________________________________________ Octave-dev mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/octave-dev
