Abstract--Expertise matching, aiming to find the alignment between experts and queries, is a common problem in many real applications such as conference paper-reviewer assignment, ...
Abstract--Commercial services for provisioning software components and virtual infrastructure in the cloud are emerging. For customers, this creates a multitude of possibilities fo...
Immanuel Trummer, Frank Leymann, Ralph Mietzner, W...
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
In a M/M/N+M queue, when there are many customers waiting, it may be preferable to reject a new arrival rather than risk that arrival later abandoning without receiving service. O...
We study the problem of maximizing the lifetime of a sensor network assigned to monitor a given area. Our main result is a linear time dual approximation algorithm that comes arbit...
In this paper, we prove some convergence properties for a class of ant colony optimization algorithms. In particular, we prove that for any small constant 0 and for a sufficiently ...
In this paper we consider stochastic programming problems where the objective function is given as an expected value of a convex piecewise linear random function. With an optimal s...
Alexander Shapiro, Tito Homem-de-Mello, Joocheol K...
We collected and analyzed a number of linear programming problems that have been shown to cycle (not converge) when solved by Dantzig's original simplex algorithm. For these ...
Dynamic programming, branch-and-bound, and constraint programming are the standard solution principles for nding optimal solutions to machine scheduling problems. We propose a new ...
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...