Zobrazeno 1 - 10
of 4 706
pro vyhledávání: '"Luo, Peng"'
Autor:
Chen, Yuyang, Luo, Peng
In this paper, we study non-homogeneous stochastic linear-quadratic (LQ) optimal control problems with multi-dimensional state and regime switching. We focus on the corresponding stochastic Riccati equation, which is the same as that one in homogeneo
Externí odkaz:
http://arxiv.org/abs/2404.00382
Autor:
Dong, Pingcheng, Tan, Yonghao, Zhang, Dong, Ni, Tianwei, Liu, Xuejiao, Liu, Yu, Luo, Peng, Liang, Luhong, Liu, Shih-Yang, Huang, Xijie, Zhu, Huaiyu, Pan, Yun, An, Fengwei, Cheng, Kwang-Ting
Non-linear functions are prevalent in Transformers and their lightweight variants, incurring substantial and frequently underestimated hardware costs. Previous state-of-the-art works optimize these operations by piece-wise linear approximation and st
Externí odkaz:
http://arxiv.org/abs/2403.19591
Autor:
Hua, Tianjiao, Luo, Peng
In this paper, we study a class of infinite horizon fully coupled McKean-Vlasov forward-backward stochastic differential equations (FBSDEs). We propose a generalized monotonicity condition involving two flexible functions. Under this condition, we es
Externí odkaz:
http://arxiv.org/abs/2403.14396
The present paper studies a kind of robust optimization problems with constraint. The problem is formulated through Backward Stochastic Differential Equations (BSDEs) with quadratic generators. A necessary condition is established for the optimal sol
Externí odkaz:
http://arxiv.org/abs/2402.08260
Urban spaces, though often perceived as discrete communities, are shared by various functional and social groups. Our study introduces a graph-based physics-aware deep learning framework, illuminating the intricate overlapping nature inherent in urba
Externí odkaz:
http://arxiv.org/abs/2402.00222
Autor:
Chen, Jinghong, Zhu, Lingxuan, Mou, Weiming, Liu, Zaoqu, Cheng, Quan, Lin, Anqi, Zhang, Jian, Luo, Peng
Generative Artificial Intelligence (AI) holds immense potential in medical applications. Numerous studies have explored the efficacy of various generative AI models within healthcare contexts, but there is a lack of a comprehensive and systematic eva
Externí odkaz:
http://arxiv.org/abs/2312.10074
Deep steganography utilizes the powerful capabilities of deep neural networks to embed and extract messages, but its reliance on an additional message extractor limits its practical use due to the added suspicion it can raise from steganalyzers. To a
Externí odkaz:
http://arxiv.org/abs/2312.04743
Autor:
Hua, Tianjiao, Luo, Peng
In this paper, we consider a class of linear quadratic extended mean field games (MFGs) with common noises where the state coefficients and the cost functional vary with the mean field term in a nonlinear way. Based on stochastic maximum principle, s
Externí odkaz:
http://arxiv.org/abs/2311.04001
Autor:
Chen, Yuyang, Luo, Peng
This paper deals with the long time behavior of the optimal solution of stochastic backward linear-quadratic optimal control problem over the finite time horizon. Both weak and strong turnpike properties are established under appropriate conditions,
Externí odkaz:
http://arxiv.org/abs/2309.03456
Autor:
Hua, Tianjiao, Luo, Peng
In this paper, we study a class of mean field type FBSDEs. We propose a class of motonotinity conditions, under which we show the uniformly Lipschitz continuity of the decoupling field and obtain the existence and uniqueness of solution. We further p
Externí odkaz:
http://arxiv.org/abs/2307.11536