Distilling common randomness from bipartite quantum states
Igor Devetak, Andreas Winter
ISIT 2003
We consider the problem of minimizing a differentiable function of n parameters, with upper and lower bounds on the parameters. The motivation for this work comes from the optimization of the design of transient electrical circuits. In such optimization, the parameters are circuit elements, the bound constraints keep these parameters physically meaningful, and both the function and gradient evaluations contain errors. We describe a quasi-Newton algorithm for such problems. This algorithm handles the box constraints directly and approximates the given function locally by nonsingular quadratic functions. Numerical tests indicate that the algorithm can tolerate the errors, if the errors in the function and gradient are of the same relative size. © 1979 Plenum Publishing Corporation.
Igor Devetak, Andreas Winter
ISIT 2003
D.S. Turaga, K. Ratakonda, et al.
SCC 2006
Ronen Feldman, Martin Charles Golumbic
Ann. Math. Artif. Intell.
Guo-Jun Qi, Charu Aggarwal, et al.
IEEE TPAMI