— This paper presents a single-objective and a multiobjective stochastic optimization algorithms for global training of neural networks based on simulated annealing. The algorith...
Abstract— The design of root-Nyquist pulses with the maximum possible energy concentration of the power spectrum is a fundamental problem is communications engineering. Since the...
We describe a scheme for solving Energy Minimization problems, which is based on the A∗ algorithm accomplished with appropriately chosen LP-relaxations as heuristic functions. Th...
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
Generalized geometric programming (GGP) is an optimization method in which the objective function and constraints are nonconvex functions. Thus, a GGP problem includes multiple lo...