no code implementations • 23 Feb 2024 • Jingtao Ding, Chang Liu, Yu Zheng, Yunke Zhang, Zihan Yu, Ruikun Li, Hongyi Chen, Jinghua Piao, Huandong Wang, Jiazhen Liu, Yong Li
Complex networks pervade various real-world systems, from the natural environment to human societies.
no code implementations • 10 Nov 2023 • Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang
Prior attempts have quantified the privacy risks of language models (LMs) via MIAs, but there is still no consensus on whether existing MIA algorithms can cause remarkable privacy leakage on practical Large Language Models (LLMs).
no code implementations • 23 Aug 2023 • Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang
Membership Inference Attack (MIA) identifies whether a record exists in a machine learning model's training set by querying the model.
1 code implementation • 19 Jul 2023 • Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li
Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist naturally in the form of networks, is of great value to us.
no code implementations • 17 Jun 2023 • Huandong Wang, Huan Yan, Can Rong, Yuan Yuan, Fenyu Jiang, Zhenyu Han, Hongjie Sui, Depeng Jin, Yong Li
In this survey, we will systematically review the literature on multi-scale simulation of complex systems from the perspective of knowledge and data.
no code implementations • 6 Jun 2023 • Can Rong, Huandong Wang, Yong Li
Origin-destination (OD) flow, which contains valuable population mobility information including direction and volume, is critical in many urban applications, such as urban planning, transportation management, etc.
no code implementations • 22 Feb 2023 • Huiming Chen, Huandong Wang, Qingyue Long, Depeng Jin, Yong Li
Based on these frameworks, we have instantiated FedOpt algorithms.
1 code implementation • 9 Feb 2023 • Yuan Yuan, Huandong Wang, Jingtao Ding, Depeng Jin, Yong Li
To enhance the fidelity and utility of the generated activity data, our core idea is to model the evolution of human needs as the underlying mechanism that drives activity generation in the simulation model.
no code implementations • 15 Dec 2021 • Huiming Chen, Huandong Wang, Quanming Yao, Yong Li, Depeng Jin, Qiang Yang
Federated optimization (FedOpt), which targets at collaboratively training a learning model across a large number of distributed clients, is vital for federated learning.
no code implementations • 1 Nov 2021 • Huandong Wang, Qiaohong Yu, Yu Liu, Depeng Jin, Yong Li
Further, a complex embedding model with elaborately designed scoring functions is proposed to measure the plausibility of facts in STKG to solve the knowledge graph completion problem, which considers temporal dynamics of the mobility patterns and utilizes PoI categories as the auxiliary information and background knowledge.