Zobrazeno 1 - 10
of 395
pro vyhledávání: '"Huang, Yijie"'
Autor:
Wang, Ming, Liu, Yuanzhong, Liang, Xiaoyu, Huang, Yijie, Wang, Daling, Yang, Xiaocui, Shen, Sijia, Feng, Shi, Zhang, Xiaoming, Guan, Chaofeng, Zhang, Yifei
LLMs have demonstrated commendable performance across diverse domains. Nevertheless, formulating high-quality prompts to assist them in their work poses a challenge for non-AI experts. Existing research in prompt engineering suggests somewhat scatter
Externí odkaz:
http://arxiv.org/abs/2409.13449
Autor:
Zhang, Yiqun, Yang, Xiaocui, Xu, Xingle, Gao, Zeran, Huang, Yijie, Mu, Shiyi, Feng, Shi, Wang, Daling, Zhang, Yifei, Song, Kaisong, Yu, Ge
Affective Computing (AC), integrating computer science, psychology, and cognitive science knowledge, aims to enable machines to recognize, interpret, and simulate human emotions.To create more value, AC can be applied to diverse scenarios, including
Externí odkaz:
http://arxiv.org/abs/2408.04638
This paper studies continuous-time reinforcement learning for controlled jump-diffusion models by featuring the q-function (the continuous-time counterpart of Q-function) and the q-learning algorithms under the Tsallis entropy regularization. Contrar
Externí odkaz:
http://arxiv.org/abs/2407.03888
Autor:
Wang, Ming, Liu, Yuanzhong, Liang, Xiaoyu, Li, Songlian, Huang, Yijie, Zhang, Xiaoming, Shen, Sijia, Guan, Chaofeng, Wang, Daling, Feng, Shi, Zhang, Huaiwen, Zhang, Yifei, Zheng, Minghui, Zhang, Chi
LLMs have demonstrated commendable performance across diverse domains. Nevertheless, formulating high-quality prompts to instruct LLMs proficiently poses a challenge for non-AI experts. Existing research in prompt engineering suggests somewhat scatte
Externí odkaz:
http://arxiv.org/abs/2402.16929
This paper studies an infinite horizon optimal tracking portfolio problem using capital injection in incomplete market models. We consider the benchmark process modelled by a geometric Brownian motion with zero drift driven by some unhedgeable risk.
Externí odkaz:
http://arxiv.org/abs/2311.14318
The success of pre-training approaches on a variety of downstream tasks has revitalized the field of computer vision. Image aesthetics assessment (IAA) is one of the ideal application scenarios for such methods due to subjective and expensive labelin
Externí odkaz:
http://arxiv.org/abs/2307.15640
This paper studies the existence and uniqueness of a classical solution to a type of Robin boundary problems on the nonnegative orthant. We propose a new decomposition-homogenization method for the Robin boundary problem based on probabilistic repres
Externí odkaz:
http://arxiv.org/abs/2306.08312
This paper studies a Merton's optimal consumption problem in an extended formulation incorporating the tracking of a benchmark process described by a geometric Brownian motion. We consider a relaxed tracking formulation such that the wealth process c
Externí odkaz:
http://arxiv.org/abs/2304.10802
Autor:
Lyu, Mengyao, Zhou, Jundong, Chen, Hui, Huang, Yijie, Yu, Dongdong, Li, Yaqian, Guo, Yandong, Guo, Yuchen, Xiang, Liuyu, Ding, Guiguang
Active learning selects informative samples for annotation within budget, which has proven efficient recently on object detection. However, the widely used active detection benchmarks conduct image-level evaluation, which is unrealistic in human work
Externí odkaz:
http://arxiv.org/abs/2303.13089
This paper studies stochastic control problems motivated by optimal consumption with wealth benchmark tracking. The benchmark process is modeled by a combination of a geometric Brownian motion and a running maximum process, indicating its increasing
Externí odkaz:
http://arxiv.org/abs/2302.08302