output
20112022
most citedOptimal Geographic Caching In Cellular Networks

471 citations

Showing eess.SYShow all

6 papers · 1 filter

eess.SY2019★ 2 cited

Zap Q-Learning for Optimal Stopping Time Problems

Shuhang Chen, Adithya M. Devraj, Ana Bušić +1

The objective in this paper is to obtain fast converging reinforcement learning algorithms to approximate solutions to the problem of discounted cost optimal stopping in an irreduc…

eess.SY2016★ 1 cited

Estimation and Control of Quality of Service in Demand Dispatch

Yue Chen, Ana Bušić, Sean Meyn

It is now well known that flexibility of energy consumption can be harnessed for the purposes of grid-level ancillary services. In particular, through distributed control of a coll…

eess.SY2015★ 16 cited

Smart Fridge / Dumb Grid? Demand Dispatch for the Power Grid of 2020

Joel Mathias, Rim Kaddah, Ana Bušić +1

In discussions at the 2015 HICSS meeting, it was argued that loads can provide most of the ancillary services required today and in the future. Through load-level and grid-level co…

eess.SY2015★ 46 cited

State Estimation for the Individual and the Population in Mean Field Control with Application to Demand Dispatch

Yue Chen, Ana Bušić, Sean Meyn

This paper concerns state estimation problems in a mean field control setting. In a finite population model, the goal is to estimate the joint distribution of the population state…

eess.SY2013★ 1 cited

Randomized Consensus with Attractive and Repulsive Links

Guodong Shi, Alexandre Proutiere, Mikael Johansson +1

We study convergence properties of a randomized consensus algorithm over a graph with both attractive and repulsive links. At each time instant, a node is randomly selected to inte…

eess.SY2012★ 5 cited

Distributed Optimization: Convergence Conditions from a Dynamical System Perspective

Guodong Shi, Alexandre Proutiere, Karl Henrik Johansson

This paper explores the fundamental properties of distributed minimization of a sum of functions with each function only known to one node, and a pre-specified level of node knowle…