no code implementations • 8 Feb 2024 • Yizhou Zhang, Lun Du, Defu Cao, Qiang Fu, Yan Liu
Foundation models, such as Large language Models (LLMs), have attracted significant amount of interest due to their large number of applications.
no code implementations • 15 Apr 2023 • Yizhou Zhang, Loc Trinh, Defu Cao, Zijun Cui, Yan Liu
Recent years have witnessed the sustained evolution of misinformation that aims at manipulating public opinions.
no code implementations • 30 Nov 2022 • Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman
In particular, we show that, despite restricting each agent's attention to only its $\kappa$-hop neighborhood, the agents are able to learn a policy with an optimality gap that decays polynomially in $\kappa$.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 14 Oct 2022 • Yizhou Zhang, Defu Cao, Yan Liu
To address these issues, in this paper, we build up a causal framework that model the causal effect of misinformation from the perspective of temporal point process.
no code implementations • NeurIPS 2021 • Yizhou Zhang, Karishma Sharma, Yan Liu
Specifically, when modeling the observed data from social media with neural temporal point process, we jointly learn a Gibbs-like distribution of group assignment based on how consistent an assignment is to (1) the account embedding space and (2) the prior knowledge.
no code implementations • 15 Jun 2021 • Karishma Sharma, Yizhou Zhang, Yan Liu
In this work, we investigate misinformation communities and narratives that can contribute to COVID-19 vaccine hesitancy.
no code implementations • 1 Jan 2021 • Yizhou Zhang, Zhaoheng Zheng, Yan Liu
Recent researches have achieved substantial advances in learning structured representations from images.
no code implementations • 3 Sep 2020 • Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla, Chuizheng Meng, Yan Liu
Epidemic spread in a population is traditionally modeled via compartmentalized models which represent the free evolution of disease in absence of any intervention policies.
2 code implementations • 3 Jun 2019 • Yizhou Zhang, Guojie Song, Lun Du, Shu-wen Yang, Yilun Jin
Recent works reveal that network embedding techniques enable many machine learning models to handle diverse downstream tasks on graph structured data.