59 citations · 63 across the 7 of their papers we have counts for
7 papers
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…
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…
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…
RCC-Dual-GAN: An Efficient Approach for Outlier Detection with Few Identified Anomalies
Zhe Li, Chunhua Sun, Chunli Liu +3
Outlier detection is an important task in data mining and many technologies have been explored in various applications. However, due to the default assumption that outliers are non…
Generative Adversarial Active Learning for Unsupervised Outlier Detection
Yezheng Liu, Zhe Li, Chong Zhou +4
Outlier detection is an important topic in machine learning and has been used in a wide range of applications. In this paper, we approach outlier detection as a binary-classificati…