Zobrazeno 1 - 10
of 237
pro vyhledávání: '"Xie, Yiqun"'
Enhancing diverse human decision-making processes in an urban environment is a critical issue across various applications, including ride-sharing vehicle dispatching, public transportation management, and autonomous driving. Offline reinforcement lea
Externí odkaz:
http://arxiv.org/abs/2406.14054
Autor:
Xie, Yiqun, Wang, Zhihao, Chen, Weiye, Li, Zhili, Jia, Xiaowei, Li, Yanhua, Wang, Ruichen, Chai, Kangyang, Li, Ruohan, Skakun, Sergii
Foundation models, i.e., very large deep learning models, have demonstrated impressive performances in various language and vision tasks that are otherwise difficult to reach using smaller-size models. The major success of GPT-type of language models
Externí odkaz:
http://arxiv.org/abs/2404.11797
When dealing with data from distinct locations, machine learning algorithms tend to demonstrate an implicit preference of some locations over the others, which constitutes biases that sabotage the spatial fairness of the algorithm. This unfairness ca
Externí odkaz:
http://arxiv.org/abs/2402.13379
Autor:
Yu, Runlong, Ladwig, Robert, Xu, Xiang, Zhu, Peijun, Hanson, Paul C., Xie, Yiqun, Jia, Xiaowei
Predicting dissolved oxygen (DO) concentrations in north temperate lakes requires a comprehensive study of phenological patterns across various ecosystems, which highlights the significance of selecting phenological features and feature interactions.
Externí odkaz:
http://arxiv.org/abs/2403.18923
Fairness-awareness has emerged as an essential building block for the responsible use of artificial intelligence in real applications. In many cases, inequity in performance is due to the change in distribution over different regions. While technique
Externí odkaz:
http://arxiv.org/abs/2401.15270
Autor:
Luo, Shiyuan, Ni, Juntong, Chen, Shengyu, Yu, Runlong, Xie, Yiqun, Liu, Licheng, Jin, Zhenong, Yao, Huaxiu, Jia, Xiaowei
Modeling environmental ecosystems is critical for the sustainability of our planet, but is extremely challenging due to the complex underlying processes driven by interactions amongst a large number of physical variables. As many variables are diffic
Externí odkaz:
http://arxiv.org/abs/2311.10255
Neural networks trained on distilled data often produce over-confident output and require correction by calibration methods. Existing calibration methods such as temperature scaling and mixup work well for networks trained on original large-scale dat
Externí odkaz:
http://arxiv.org/abs/2307.12463
Human mobility estimation is crucial during the COVID-19 pandemic due to its significant guidance for policymakers to make non-pharmaceutical interventions. While deep learning approaches outperform conventional estimation techniques on tasks with ab
Externí odkaz:
http://arxiv.org/abs/2301.08648
Autor:
Li, Yan, Yang, Mingzhou, Eagon, Matthew, Farhadloo, Majid, Xie, Yiqun, Northrop, William F., Shekhar, Shashi
The eco-toll estimation problem quantifies the expected environmental cost (e.g., energy consumption, exhaust emissions) for a vehicle to travel along a path. This problem is important for societal applications such as eco-routing, which aims to find
Externí odkaz:
http://arxiv.org/abs/2301.05739
Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These applications greatly rely on regional features that characterize spati
Externí odkaz:
http://arxiv.org/abs/2212.06864