As application complexity increases, modern embedded systems have adopted heterogeneous processing elements to enhance the computing capability or to reduce the power consumption. ...
In this paper, we study the spread of influence through a social network, in a model initially studied by Kempe, Kleinberg and Tardos [14, 15]: We are given a graph modeling a soc...
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
Bin covering takes as input a list of items with sizes in (0 1) and places them into bins of unit demand so as to maximize the number of bins whose demand is satis ed. This is in ...
This paper explores an approach to global, stochastic, simulation optimization which combines stochastic approximation (SA) with simulated annealing (SAN). SA directs a search of ...