16 citations · 24 across the 10 of their papers we have counts for
10 papers
Adversarially Robust Detection of Harmful Online Content: A Computational Design Science Approach
Yidong Chai, Yi Liu, Mohammadreza Ebrahimi +2
Social media platforms are plagued by harmful content such as hate speech, misinformation, and extremist rhetoric. Machine learning (ML) models are widely adopted to detect such co…
AI Chatbots as Professional Service Agents: Developing a Professional Identity
Wenwen Li, Kangwei Shi, Yidong Chai
With the rapid expansion of large language model (LLM) applications, there is an emerging shift in the role of LLM-based AI chatbots from serving merely as general inquiry tools to…
Detecting Fake News on Social Media: A Novel Reliability Aware Machine-Crowd Hybrid Intelligence-Based Method
Yidong Chai, Kangwei Shi, Jiaheng Xie +3
Fake news on social media platforms poses a significant threat to societal systems, underscoring the urgent need for advanced detection methods. The existing detection methods can…
From Machine Learning to Machine Unlearning: Complying with GDPR's Right to be Forgotten while Maintaining Business Value of Predictive Models
Yuncong Yang, Xiao Han, Yidong Chai +3
Recent privacy regulations (e.g., GDPR) grant data subjects the `Right to Be Forgotten' (RTBF) and mandate companies to fulfill data erasure requests from data subjects. However, c…
Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble Deep Kernel Learning Model
Yonghang Zhou, Hongyi Zhu, Yidong Chai +2
Web attacks are one of the major and most persistent forms of cyber threats, which bring huge costs and losses to web application-based businesses. Various detection methods, such…
A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning
Anqi Zhou, Yezheng Liu, Yidong Chai +4
Federated Learning (FL) has garnered widespread adoption across various domains such as finance, healthcare, and cybersecurity. Nonetheless, FL remains under significant threat fro…
Emotion-aware Personalized Music Recommendation with a Heterogeneity-aware Deep Bayesian Network
Erkang Jing, Yezheng Liu, Yidong Chai +4
Music recommender systems play a critical role in music streaming platforms by providing users with music that they are likely to enjoy. Recent studies have shown that user emotion…
Heterogeneous Domain Adaptation with Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity
Mohammadreza Ebrahimi, Yidong Chai, Hao Helen Zhang +1
Learning predictive models in new domains with scarce training data is a growing challenge in modern supervised learning scenarios. This incentivizes developing domain adaptation m…
TopicModel4J: A Java Package for Topic Models
Yang Qian, Yuanchun Jiang, Yidong Chai +2
Topic models provide a flexible and principled framework for exploring hidden structure in high-dimensional co-occurrence data and are commonly used natural language processing (NL…
Deep Learning for Information Systems Research
Sagar Samtani, Hongyi Zhu, Balaji Padmanabhan +2
Artificial Intelligence (AI) has rapidly emerged as a key disruptive technology in the 21st century. At the heart of modern AI lies Deep Learning (DL), an emerging class of algorit…