The diverse world of machine learning applications has given rise to a plethora of algorithms and optimization methods, finely tuned to the specific regression or classification task at hand. We reduce the complexity of algorithm design for machine learning by reductions: we develop reductions that take a method developed for one setting and apply it to the entire spectrum of smoothness and str...

This paper addresses the problem of designing objective functions for autonomous surveillance—target search & tracking (S&T)—by unmanned aerial vehicles (UAVs). A typical S&T mission inherently includes multiple, most often conflicting, objectives such as detection, survival, and tracking. A common approach to cope with this issue is to optimize a convex combination (weighted sum) of the indivi...

An optimization approach to distributed intelligent system design and control is presented. It is expected to enhance the autonomous decisionmaking capabilities of subsystems. It is applicable to autonomous multiple agents homogeneous or heterogeneous clusters, when they must collaborate to achieve a common goal, acting in a coordinated manner that will provide situation awareness, collision av...

We present an application of multiple-objectives evolutionary optimization to the problem of engineering the distribution of the interdomain traffic in the Internet. We show that this practical problem requires such a heuristic due to the potential conflicting nature of the traffic engineering objectives. Furthermore, having to work on the parameter’s space of the real problem makes such techni...

There has been a surge of research interest in developing tools and analysis for Bayesian optimization, the task of finding the global maximizer of an unknown, expensive function through sequential evaluation using Bayesian decision theory. However, many interesting problems involve optimizing multiple, expensive to evaluate objectives simultaneously, and relatively little research has addresse...

this study concerns the scope to improve water flooding in heterogeneous reservoirs. we used an existing, in-house developed, optimization program consisting of a reservoir simulator in combination with an adjoint-based optimal control algorithm. in particular we aimed to examine the scope for optimization in a two-dimensional horizontal reservoir containing a single high permeable streak, as a...

With the increasing usage of QoS-based applications, traffic engineering in communication networks has become more crucial. For the optimal utilization of network resources, service providers need to consider multiple criteria that can be customeror traffic-oriented. Multiprotocol Label Switching (MPLS) has been developed to apply more convenient traffic engineering in autonomous systems. This ...

Due to the significant advancement of the unmanned vehicle (UV) technologies in recent years, a great deal of research effort has been devoted to the problem of path optimization (planning and dynamic replanning) of a single or multiple UVs in uncertain and possibly hostile environments. While various UV mission scenarios have been considered in the literature, this paper is focused on UAV surv...