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We prove a conjecture of Lecouvey, which proposes a closed, positive combinatorial formula for symplectic Kostka-Foulkes polynomials, in the case of rows of arbitrary weight. To show this, we construct a new algorithm for computing cocyclage in terms of wh ...
We consider various versions of the obstacle and thin-obstacle problems, we interpret them as variational inequalities, with non-smooth constraint, and prove that they satisfy a new constrained Lojasiewicz inequality. The difficulty lies in the fact that, ...
The next technological revolution will be interwoven to the proliferation of intelligent systems. As we bridge the gap between physical and cyber worlds, we will give rise to large-scale, multi-agent based technologies. A key challenge that cities of the f ...
As more private firms participate in public projects aiming to increase their profits by adjusting operational strategies, there has been an increasing demand for structural identification in the operational phase. In this paper, we propose a framework for ...
The COVID-19 pandemic created a noticeable challenge to the cryptographic community with the development of contact tracing applications. The media reported a dispute between designers proposing a centralized or a decentralized solution (namely, the PEPP-P ...
Phasor data concentrators (PDCs) are essential functions in synchrophasor networks that collect and aggregate phasor measurement unit (PMU) data from across the electric grid. PDC buffers synchrophasor datasets during the “wait time” period, then communica ...
This paper investigates reverse auctions that involve continuous values of different types of goods, general nonconvex constraints, and second stage costs. We seek to design the payment rules and conditions under which coalitions of participants cannot inf ...
We present constraints on local primordial non-Gaussianity (PNG), parametrized through f(NL)(loc), using the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. We measure and analyze the anisotropic ...
Neural networks are increasingly used in complex (data-driven) simulations as surrogates or for accelerating the computation of classical surrogates. In many applications physical constraints, such as mass or energy conservation, must be satised to obtain ...
We consider multiagent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we propose a novel dis ...
