Zobrazeno 1 - 10
of 2 789
pro vyhledávání: '"Nan, Jing"'
This paper is devoted to the study of acceleration methods for an inequality constrained convex optimization problem by using Lyapunov functions. We first approximate such a problem as an unconstrained optimization problem by employing the logarithmi
Externí odkaz:
http://arxiv.org/abs/2411.14828
This paper investigates the initial boundary value problem of finitely degenerate semilinear pseudo-parabolic equations associated with H\"{o}rmander's operator. For the low and critical initial energies, based on the global existence of solutions in
Externí odkaz:
http://arxiv.org/abs/2411.12253
The main goal of this paper is to investigate the multi-parameter stability result for a stochastic fractional differential variational inequality with L\'{e}vy jump (SFDVI with L\'{e}vy jump) under some mild conditions. We verify that Mosco converge
Externí odkaz:
http://arxiv.org/abs/2411.07557
This paper provides the upper and lower bounds of blowup time and blowup rate as well as the exponential growth estimate of blowup solutions for a pseudo-parabolic equation with singular potential. These results complement the ones obtained in the pr
Externí odkaz:
http://arxiv.org/abs/2405.11707
In this paper, we first establish the separation theorem between a point and a locally geodesic convex set and then prove the existence of a supporting quasi-hyperplane at any point on the boundary of the closed locally geodesic convex set on a Riema
Externí odkaz:
http://arxiv.org/abs/2401.13316
This paper studies linear quadratic graphon mean field games (LQ-GMFGs) with common noise, in which a large number of agents are coupled via a weighted undirected graph. One special feature, compared with the well-studied graphon mean field games, is
Externí odkaz:
http://arxiv.org/abs/2401.09030
Data-driven soft sensors provide a potentially cost-effective and more accurate modeling approach to measure difficult-to-measure indices in industrial processes compared to mechanistic approaches. Artificial intelligence (AI) techniques, such as dee
Externí odkaz:
http://arxiv.org/abs/2312.12022
In this paper, by extending the classic stochastic integrals, we investigate three kinds of more general stochastic integrals: Lebesgue-Stieltjes integrals on predictable sets of interval type (in short: PSITs), stochastic integrals on PSITs of predi
Externí odkaz:
http://arxiv.org/abs/2311.03984
This paper considers consumption and portfolio optimization problems with recursive preferences in both infinite and finite time regions. Specially, the financial market consists of a risk-free asset and a risky asset that follows a general stochasti
Externí odkaz:
http://arxiv.org/abs/2307.16365
This paper introduces an Interpretable Neural Network (INN) incorporating spatial information to tackle the opaque parameterization process of random weighted neural networks. The INN leverages spatial information to elucidate the connection between
Externí odkaz:
http://arxiv.org/abs/2307.00185