Dear all,
LBFGS is not functioning the way it is.
When I had given the function to optimize i.e Square function (X-6)^2 + (Y-6)^2 instead of rosenbrock in test cases, it is not converging to [6,6] with optimal function value close to 0.
More over the hessian in LBFGS should be a square matrix of the dimension of the input vector, where as in the current implementation, it is taking it as scalar.
Please go through the implementation of BFGS  implementation in the following request
https://books.google.co.il/books?id=2B9LUYAP3n4C&lpg=PR1&ots=_8TivuY2uM&dq=nocedal%20wright%20numerical%20optimization&hl=en&pg=PR1#v=onepage&q=&f=false 22
Could you please let me know if I can have a discussion with you regarding this issue so that I can explain exactly what’s the issue and can make a pull request for this algorithm?