Areg Karapetyan

TL;DR: Practical limits to the predictability of life outcomes in some settings are suggested and the value of mass collaborations in the social sciences is illustrated.

TL;DR: This paper presents a competitive randomized online algorithm for deciding whether a sequence of inelastic demands can be allocated for the requested intervals, subject to the total satisfiable apparent power within a time-varying capacity constraint.

TL;DR: A novel theoretical guarantee is derived of the gap between the proposed efficient algorithm and the optimal solution (that may be computationally hard to obtain) is derived.

TL;DR: In this article, the authors proposed an efficient approximation algorithm for event-based demand response management in micro-grids, which can rapidly determine a close-to-optimal load curtailment scheme to maximize the aggregate customer utility in milliseconds for a large number of customers.

TL;DR: In this article, the trade-off between privacy and optimality in centralized demand response (DR) systems for maximizing cumulative customer utility is investigated, and the privacy cost is evaluated in terms of changes in objective value of the DR optimization problem when effecting the employed privacy-preserving strategy based on Laplace mechanism.