Uniform random generators deliver a simple empirical means to estimate the average complexity of an algorithm. We present a general rejection algorithm that generates sequential l...
We develop a projected-subgradient primal-dual Lagrange optimization for global placement, that can be instantiated with a variety of interconnect models. It decomposes the origin...
We study how different prediction update algorithms influence the performance of XCSF. We consider three classical parameter estimation algorithms (NLMS, RLS, and Kalman filter) a...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
The paper presents distributed and parallel -approximation algorithms for covering problems, where is the maximum number of variables on which any constraint depends (for example...
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...