This paper proposes a novel adaptive representation for evolutionary multiobjective optimization for solving a stock modeling problem. The standard Pareto Achieved Evolution Strat...
Mihai Oltean, Crina Grosan, Ajith Abraham, Mario K...
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
— The dynamic nature of ad hoc networks advocates the use of adaptive schemes to optimize network performance. Such adaptive schemes require local observations of prevailing netw...
— In this paper, an optimization-based adaptive Kalman filtering method is proposed. The method produces an estimate of the process noise covariance matrix Q by solving an optim...
In this paper we present a clustered, multiple-clock domain (CMCD) microarchitecture that combines the benefits of both clustering and Globally Asynchronous Locally Synchronous (G...