Zobrazeno 1 - 10
of 877
pro vyhledávání: '"GAO Xuefeng"'
Autor:
Jiang Xin, Deng Bin, Gao Xuefeng, Zhang Yun, Li Guangyao, Li Guiqing, She Qiang, Ding Yanbing
Publikováno v:
Open Medicine, Vol 18, Iss 1, Pp 868-76 (2023)
This research aimed to evaluate the eradication efficacy, safety, and gastrointestinal symptom relief rates of empirical bismuth quadruple therapy, high-dose dual therapy, and resistance gene-based triple therapy in primary eradication patients in Ya
Externí odkaz:
https://doaj.org/article/53a61fc66151440d8f17edaf3a152800
Publikováno v:
口腔疾病防治, Vol 29, Iss 9, Pp 591-595 (2021)
Objective To explore the effects of two hemostatic agents on the bonding strength of different bonding systems in primary tooth dentin. Methods Seventy-two retained deciduous teeth were randomly selected. Forty-eight teeth were used to construct the
Externí odkaz:
https://doaj.org/article/d7be029fa81c493a9900021a0d3b5a91
We propose a new reinforcement learning (RL) formulation for training continuous-time score-based diffusion models for generative AI to generate samples that maximize reward functions while keeping the generated distributions close to the unknown tar
Externí odkaz:
http://arxiv.org/abs/2409.04832
Risk-sensitive linear quadratic regulator is one of the most fundamental problems in risk-sensitive optimal control. In this paper, we study online adaptive control of risk-sensitive linear quadratic regulator in the finite horizon episodic setting.
Externí odkaz:
http://arxiv.org/abs/2406.05366
Intensity control is a type of continuous-time dynamic optimization problems with many important applications in Operations Research including queueing and revenue management. In this study, we adapt the reinforcement learning framework to intensity
Externí odkaz:
http://arxiv.org/abs/2406.05358
Publikováno v:
E3S Web of Conferences, Vol 441, p 01016 (2023)
With a high percentage of new energy scenarios, it has become a trend for flexible resources such as energy storage systems to participate in long-term planning. In this context, it is important to explore how energy storage systems are configured. T
Externí odkaz:
https://doaj.org/article/3c2c21b674384ca093bab5fa9880c9fa
We study continuous-time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump-diffusion processes. We formulate an entropy-regularized exploratory control problem with stochastic policies to capture the exp
Externí odkaz:
http://arxiv.org/abs/2405.16449
When two players are engaged in a repeated game with unknown payoff matrices, they may be completely unaware of the existence of each other and use multi-armed bandit algorithms to choose the actions, which is referred to as the ``blindfolded game''
Externí odkaz:
http://arxiv.org/abs/2405.17463
Autor:
Gao, Xuefeng, Zhu, Lingjiong
Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications. While various fast ODE-based samplers have been proposed in the literature and employed in prac
Externí odkaz:
http://arxiv.org/abs/2401.17958
Score-based generative models (SGMs) is a recent class of deep generative models with state-of-the-art performance in many applications. In this paper, we establish convergence guarantees for a general class of SGMs in 2-Wasserstein distance, assumin
Externí odkaz:
http://arxiv.org/abs/2311.11003