Zobrazeno 1 - 10
of 574
pro vyhledávání: '"Chen Xingyuan"'
Publikováno v:
网络与信息安全学报, Vol 10, Pp 91-106 (2024)
Federated learning, capable of training models by sharing gradient parameters, faces the risk of dishonest data aggregation by malicious servers during the model aggregation process. Untrusted users participating in federated learning may also pose a
Externí odkaz:
https://doaj.org/article/4366724850b548969d78fe2a22e74e45
The pre-training cost of large language models (LLMs) is prohibitive. One cutting-edge approach to reduce the cost is zero-shot weight transfer, also known as model growth for some cases, which magically transfers the weights trained in a small model
Externí odkaz:
http://arxiv.org/abs/2408.08681
Autor:
Chen Xingyuan, Qiu Chen
Publikováno v:
Allergy, Asthma & Clinical Immunology, Vol 16, Iss 1, Pp 1-7 (2020)
Abstract Background Neutrophils, eosinophils and inflammatory cells contribute to asthmatic inflammation. The anti-bactericidal/permeability-increasing protein (BPI), produced by neutrophils, peripheral blood monocytes or epithelial cells, can neutra
Externí odkaz:
https://doaj.org/article/f522f8bfc4b2491095e58dd1b5178bf9
We study the weak convergence behaviour of the Leimkuhler--Matthews method, a non-Markovian Euler-type scheme with the same computational cost as the Euler scheme, for the approximation of the stationary distribution of a one-dimensional McKean--Vlas
Externí odkaz:
http://arxiv.org/abs/2405.01346
Wildfire significantly disturb ecosystems by altering forest structure, vegetation ecophysiology, and soil properties. Understanding the complex interactions between topographic and climatic conditions in post-wildfire recovery is crucial. This study
Externí odkaz:
http://arxiv.org/abs/2404.16834
Autor:
Li, Yueyuan, Zhang, Songan, Jiang, Mingyang, Chen, Xingyuan, Qian, Yeqiang, Wang, Chunxiang, Yang, Ming
Simulation is a prospective method for generating diverse and realistic traffic scenarios to aid in the development of driving decision-making systems. However, existing simulators often fall short in diverse scenarios or interactive behavior models
Externí odkaz:
http://arxiv.org/abs/2311.11058
The complex Helmholtz equation $(\Delta + k^2)u=f$ (where $k\in{\mathbb R},u(\cdot),f(\cdot)\in{\mathbb C}$) is a mainstay of computational wave simulation. Despite its apparent simplicity, efficient numerical methods are challenging to design and, i
Externí odkaz:
http://arxiv.org/abs/2308.11469
The deep neural network has attained significant efficiency in image recognition. However, it has vulnerable recognition robustness under extensive data uncertainty in practical applications. The uncertainty is attributed to the inevitable ambient no
Externí odkaz:
http://arxiv.org/abs/2308.00346
We study a class of McKean--Vlasov Stochastic Differential Equations (MV-SDEs) with drifts and diffusions having super-linear growth in measure and space -- the maps have general polynomial form but also satisfy a certain monotonicity condition. The
Externí odkaz:
http://arxiv.org/abs/2302.05133
Autor:
Chen, Xingyuan, Reis, Goncalo dos
We consider in this work the convergence of a split-step Euler type scheme (SSM) for the numerical simulation of interacting particle Stochastic Differential Equation (SDE) systems and McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with fu
Externí odkaz:
http://arxiv.org/abs/2208.12772