no code implementations • CONSTRAINT (ACL) 2022 • Jason Lucas, Limeng Cui, Thai Le, Dongwon Lee
The COVID-19 pandemic has created threats to global health control.
no code implementations • 27 Mar 2024 • Yanshen Sun, Jianfeng He, Limeng Cui, Shuo Lei, Chang-Tien Lu
Studies highlight the gap in the deceptive power of LLM-generated fake news with and without human assistance, yet the potential of prompting techniques has not been fully explored.
no code implementations • 9 Mar 2024 • Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang
E-commerce platforms typically store and structure product information and search data in a hierarchy.
no code implementations • 14 Jun 2023 • Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang
Therefore, in this work, we study a novel problem of developing robust and membership privacy-preserving GNNs.
1 code implementation • 13 Oct 2021 • Jiangshu Du, Yingtong Dou, Congying Xia, Limeng Cui, Jing Ma, Philip S. Yu
The COVID-19 pandemic poses a great threat to global public health.
no code implementations • 1 Jan 2021 • Limeng Cui, Aaron Jaech
We re-examine Routing Networks, an approach to multi-task learning that uses reinforcement learning to decide parameter sharing with the goal of maximizing knowledge transfer between related tasks while avoiding task interference.
2 code implementations • 22 May 2020 • Limeng Cui, Dongwon Lee
As the COVID-19 virus quickly spreads around the world, unfortunately, misinformation related to COVID-19 also gets created and spreads like wild fire.
no code implementations • 26 Nov 2019 • Limeng Cui, Siddharth Biswal, Lucas M. Glass, Greg Lever, Jimeng Sun, Cao Xiao
How to further leverage patients with possibly uncertain diagnosis to improve detection?
no code implementations • ICLR 2019 • Jiawei Zhang, Limeng Cui, Fisher B. Gouza
Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years.
no code implementations • 22 May 2018 • Jiawei Zhang, Limeng Cui, Fisher B. Gouza
To address the problem, a novel generative model, namely EgoCoder, will be introduced in this paper.
no code implementations • 19 May 2018 • Jiawei Zhang, Limeng Cui, Fisher B. Gouza
In this paper, we aim at introducing a new machine learning model, namely reconciled polynomial machine, which can provide a unified representation of existing shallow and deep machine learning models.
no code implementations • 19 May 2018 • Jiawei Zhang, Limeng Cui, Fisher B. Gouza
In this paper, we propose to provide a general ensemble learning framework based on deep learning models.
no code implementations • 19 May 2018 • Jiawei Zhang, Limeng Cui, Fisher B. Gouza
In this paper, we introduce an alternative approach, namely GEN (Genetic Evolution Network) Model, to the deep learning models.
1 code implementation • 23 Mar 2018 • Jiawei Zhang, Limeng Cui, Fisher B. Gouza
Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years.
no code implementations • 26 Nov 2017 • Jiawei Zhang, Congying Xia, Chenwei Zhang, Limeng Cui, Yanjie Fu, Philip S. Yu
The closeness among users in the networks are defined as the meta proximity scores, which will be fed into DIME to learn the embedding vectors of users in the emerging network.
Social and Information Networks Databases
no code implementations • IEEE Transactions on Intelligent Transportation Systems 2016 • Yong Shi, Limeng Cui, Zhiquan Qi, Fan Meng, and Zhensong Chen
Our contributions are shown as follows: 1) apply the integral channel features to redefine the tokens that constitute a crack and get better representation of the cracks with intensity inhomogeneity; 2) introduce random structured forests to generate a high- performance crack detector, which can identify arbitrarily com- plex cracks; and 3) propose a new crack descriptor to characterize cracks and discern them from noises effectively.