Yidong Chai

Orcid: 0000-0003-0260-7589

According to our database1, Yidong Chai authored at least 53 papers between 2017 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Balancing Imperceptible and Aggressive Poisoning Attack for Recommender Systems: A Simple Multinomial Diffusion Model.
ACM Trans. Inf. Syst., May, 2026

Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model.
Inf. Syst. Res., 2026

A disentangled multimodal neural topic model.
Inf. Process. Manag., 2026

Toward trustworthy web attack detection: An uncertainty-aware ensemble deep kernel learning model.
Inf. Manag., 2026

2025
A deep learning model integrating domain-specific features for enhanced glaucoma diagnosis.
BMC Medical Informatics Decis. Mak., December, 2025

When Experts Speak:Sequential LLM-Bayesian Learning for Startup Success Prediction.
CoRR, December, 2025

Adversarially Robust Detection of Harmful Online Content: A Computational Design Science Approach.
CoRR, December, 2025

Collaborative Management for Chronic Diseases and Depression: A Double Heterogeneity-based Multi-Task Learning Method.
CoRR, November, 2025

Emotion-aware Personalized Music Recommendation with a Heterogeneity-aware Deep Bayesian Network.
ACM Trans. Inf. Syst., September, 2025

A Bayesian Hybrid Parameter-Efficient Fine-Tuning Method for Large Language Models.
CoRR, August, 2025

RADAR: A Framework for Developing Adversarially Robust Cyber Defense AI Agents with Deep Reinforcement Learning.
MIS Q., 2025

AI Chatbots as Professional Service Agents: Developing a Professional Identity.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

2024
An interpretable wide and deep model for online disinformation detection.
Expert Syst. Appl., March, 2024

Product consumptions meet reviews: Inferring consumer preferences by an explainable machine learning approach.
Decis. Support Syst., February, 2024

Motion Sensor-Based Fall Prevention for Senior Care: A Hidden Markov Model with Generative Adversarial Network Approach.
Inf. Syst. Res., 2024

A Bayesian deep recommender system for uncertainty-aware online physician recommendation.
Inf. Manag., 2024

A profile similarity-based personalized federated learning method for wearable sensor-based human activity recognition.
Inf. Manag., 2024

Review-based recommendation under preference uncertainty: An asymmetric deep learning framework.
Eur. J. Oper. Res., 2024

Detecting Fake News on Social Media: A Novel Reliability Aware Machine-Crowd Hybrid Intelligence-Based Method.
CoRR, 2024

From Machine Learning to Machine Unlearning: Complying with GDPR's Right to be Forgotten while Maintaining Business Value of Predictive Models.
CoRR, 2024

Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble Deep Kernel Learning Model.
CoRR, 2024

A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning.
CoRR, 2024

Personalized Music Recommendation with a Heterogeneity-aware Deep Bayesian Network.
CoRR, 2024

Few-Shot Learning for Chronic Disease Management: Leveraging Large Language Models and Multi-Prompt Engineering with Medical Knowledge Injection.
CoRR, 2024

Enhancing Adversarial Robustness: A Novel Bayesian Uncertainty-Based Ensemble Learning Method.
Proceedings of the 9th IEEE International Conference on Data Science in Cyberspace, 2024

2023
Additive Feature Attribution Explainable Methods to Craft Adversarial Attacks for Text Classification and Text Regression.
IEEE Trans. Knowl. Data Eng., December, 2023

A deep interpretable representation learning method for speech emotion recognition.
Inf. Process. Manag., November, 2023

A Multi-Label Classification with an Adversarial-Based Denoising Autoencoder for Medical Image Annotation.
ACM Trans. Manag. Inf. Syst., June, 2023

Why some products compete and others don't: A competitive attribution model from customer perspective.
Decis. Support Syst., June, 2023

Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Unbox the Black-Box: Predict and Interpret YouTube Viewership Using Deep Learning.
J. Manag. Inf. Syst., 2023

Deep Learning for Information Systems Research.
J. Manag. Inf. Syst., 2023

Assessing and Enhancing Adversarial Robustness for Review-Based Recommender System: A Design Science Approach.
Proceedings of the 27th Pacific Asia Conference on Information Systems, 2023

2022
Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence: An Attention-Based Deep Structured Semantic Model.
MIS Q., May, 2022

Cross-Lingual Cybersecurity Analytics in the International Dark Web with Adversarial Deep Representation Learning.
MIS Q., May, 2022

An Explainable Multi-Modal Hierarchical Attention Model for Developing Phishing Threat Intelligence.
IEEE Trans. Dependable Secur. Comput., 2022

Assessing and Enhancing Adversarial Robustness of Predictive Analytics: An Empirically Tested Design Framework.
J. Manag. Inf. Syst., 2022

Popularity prediction for marketer-generated content: A text-guided attention neural network for multi-modal feature fusion.
Inf. Process. Manag., 2022

Identification of Key Features for VR Applications with VREVIEW: A Topic Model Approach.
Proceedings of the 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, 2022

An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

An Interpretable Deep Learning Approach to Understand Health Misinformation Transmission on YouTube.
Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

2021
Fall Detection with Wearable Sensors: A Hierarchical Attention-based Convolutional Neural Network Approach.
J. Manag. Inf. Syst., 2021

Glaucoma diagnosis in the Chinese context: An uncertainty information-centric Bayesian deep learning model.
Inf. Process. Manag., 2021

Understanding Health Misinformation Transmission: An Interpretable Deep Learning Approach to Manage Infodemics.
CoRR, 2021

Dynamic Topic Model for Tracking Topic Evolution and Measuring Popularity of Scientific Literature.
Proceedings of the Sixth IEEE International Conference on Data Science in Cyberspace, 2021

2020
TopicModel4J: A Java Package for Topic Models.
CoRR, 2020

Deep Learning for Information Systems Research.
CoRR, 2020

A new convolutional neural network model for peripapillary atrophy area segmentation from retinal fundus images.
Appl. Soft Comput., 2020

Detecting Cyber Threats in Non-English Hacker Forums: An Adversarial Cross-Lingual Knowledge Transfer Approach.
Proceedings of the 2020 IEEE Security and Privacy Workshops, 2020

2019
Towards Deep Learning Interpretability: A Topic Modeling Approach.
Proceedings of the 40th International Conference on Information Systems, 2019

2018
Glaucoma diagnosis based on both hidden features and domain knowledge through deep learning models.
Knowl. Based Syst., 2018

2017
Extracting Visual Words from Images for Effective Medical Image Analysis.
Proceedings of the 21st Pacific Asia Conference on Information Systems, 2017

Deep Learning Through Two-Branch Convolutional Neuron Network for Glaucoma Diagnosis.
Proceedings of the Smart Health - International Conference, 2017


  Loading...