Task offloading in edge computing becomes significantly more challenging when applications are modeled as Directed Acyclic Graphs (DAGs), where task dependen...

To meet the increasing demand for low-latency processing in mobile and IoT devices, edge computing offloads user application tasks to nearby cloudlets (edge ...

We investigate a state estimation problem for a linear time-invariant Gaussian system, based on a measured scalar privacy-sensitive signal. This is formulate...

Large Language Models (LLMs) are increasingly used as proxies for human respondents in social science, behavioral, and marketing experiments, yet their synth...

We study the solution of symmetric positive-definite linear systems by way of families of full- and limited-memory methods. Our contributions are threefol...

The almost supermartingale convergence theorem of Robbins and Siegmund (1971) is a fundamental tool for establishing the convergence of various stochastic it...

Optical transport networks (OTNs) carry Ethernet traffic over lightpaths that can be provisioned using elastic optical networks (EONs) with flexible spectrum...

We consider the penalized security-constrained optimal power flow (SCOPF) problem in a linearized form where thermal line limits are enforced as soft constr...

This paper investigates mean field games and control on sparse networks. In the case of large expander graphs, the limit topologies are analyzed using the gr...

The design of tactical wireless networks reflects a complex interplay among structural constraints, technological choices, and underlying modeling assumption...

Tactical wireless networks play a vital role in ensuring reliable connectivity in scenarios where conventional telecommunications infrastructure is unavailab...

Bilevel optimization involves an upper-level and a lower-level decision maker. The lower-level optimization problem is nested within the constraints of the ...

In this paper, we study a finitely repeated Prisoner's Dilemma in which players are asymmetric in both their temptation to deviate from cooperation and the...

Wind power generation represents one of the main resources of modern renewable power systems. Its deployment is governed by numerous factors, e.g., weather p...

We study the solution of large symmetric positive-definite linear systems in a matrix-free setting with a limited iteration budget. We focus on the precondi...

The \(k\)-means algorithm is one of the most widely used methods for solving the minimum sum-of-squares clustering (MSSC) problem, but it is well known to ...

Aircraft design relies heavily on solving challenging and computationally expensive Multidisciplinary Design Optimization problems. In this context, there ha...

In simulation-based engineering, design choices are often obtained following the optimization of complex blackbox models. These models frequently involve mi...

The use of transfer learning within Bayesian optimization addresses the disadvantages of the so-called cold start problem by using source data to aid in th...

Predicting the state of the weather, from tracking hurricanes and thunderstorms to assessing daily temperatures, is of crucial importance. Over the past deca...