Xiaorui Liu

发表

A Double Residual Compression Algorithm for Efficient Distributed Learning

Xiaorui Liu, Yao Li, Jiliang Tang, 2019, AISTATS.

Deep Adversarial Network Alignment pdf

Jiejun Xu, Jiliang Tang, Xiaorui Liu, 2019, CIKM.

Graph Structure Learning for Robust Graph Neural Networks

Suhang Wang, Jiliang Tang, Xiaorui Liu, 2020, KDD.

Epidemic Graph Convolutional Network

Charu C. Aggarwal, Jiliang Tang, Wenqi Fan, 2020, WSDM.

Trustworthy AI: A Computational Perspective pdf

Jiliang Tang, Wenqi Fan, Xiaorui Liu, 2021, ACM Trans. Intell. Syst. Technol..

Elastic Graph Neural Networks

Jiliang Tang, Yao Ma, Xiaorui Liu, 2021, ICML.

To be Robust or to be Fair: Towards Fairness in Adversarial Training pdf

Jiliang Tang, Xiaorui Liu, Han Xu, 2020, ICML.

A Survey on Dialogue Systems: Recent Advances and New Frontiers pdf

Jiliang Tang, Dawei Yin, Hongshen Chen, 2017, SKDD.

A Double Residual Compression Algorithm for Efficient Distributed Learning

Xiaorui Liu, Yao Li, Jiliang Tang, 2019, AISTATS.

Is Homophily a Necessity for Graph Neural Networks? pdf

Jiliang Tang, Yao Ma, Xiaorui Liu, 2021, ICLR.

A Unified View on Graph Neural Networks as Graph Signal Denoising

Jiliang Tang, Yao Ma, Xiaorui Liu, 2020, CIKM.

Weight Loss Prediction in Social-Temporal Context

Jiliang Tang, Dawei Yin, Zhiwei Wang, 2019, 2019 IEEE International Conference on Healthcare Informatics (ICHI).

Linear Convergent Decentralized Optimization with Compression pdf

Jiliang Tang, Yao Li, Xiaorui Liu, 2020, ICLR.

A novel dual-modal emotion recognition algorithm with fusing hybrid features of audio signal and speech context

Xiaorui Liu, Hang Su, Yurui Xu, 2022, Complex & Intelligent Systems.

Cyber-Physical Energy Systems Security: Threat Modeling, Risk Assessment, Resources, Metrics, and Case Studies

Charalambos Konstantinou, Ioannis Zografopoulos, Juan Ospina, 2021, IEEE Access.

Primary Study on the Face-recognition Framework with anti-spoofing function

Xiaorui Liu, Xiao Wu, Dekang Zhang, 2022, 2022 4th International Conference on Data Intelligence and Security (ICDIS).

An intelligent recognition framework of access control system with anti-spoofing function

Xiaorui Liu, Guijin Ma, Dongzhihan Wang, 2022, AIMS Mathematics.

Enhancing Adversarial Training with Feature Separability

Xiaorui Liu, Xiaorui Liu, Jiliang Tang, 2022, ArXiv.

Imbalanced Adversarial Training with Reweighting pdf

Bhavani Thuraisingham, Jiliang Tang, Xiaorui Liu, 2021, 2022 IEEE International Conference on Data Mining (ICDM).

Towards the Memorization Effect of Neural Networks in Adversarial Training pdf

Jiliang Tang, Xiaorui Liu, Han Xu, 2021, ArXiv.

Automated Self-Supervised Learning for Graphs

Xiaorui Liu, Jiliang Tang, Xiangyu Zhao, 2021, ICLR.

On the Feasibility of Load-Changing Attacks in Power Systems During the COVID-19 Pandemic

Charalambos Konstantinou, Juan Ospina, Yury Dvorkin, 2020, IEEE Access.

Is Homophily a Necessity for Graph Neural Networks?

Xiaorui Liu, Jiliang Tang, Neil Shah, 2021, ICLR.

A Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems pdf

Yier Jin, Raj Gautam Dutta, Charalambos Konstantinou, 2020, IET Smart Grid.

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems

Juan Ospina, Charalambos Konstantinou, XiaoRui Liu, 2020, IEEE Access.

Large-Scale Graph Neural Networks: The Past and New Frontiers

Xiaorui Liu, Jiliang Tang, Haoyu Han, 2023, KDD.

Data-Driven Cyberphysical Anomaly Detection for Microgrids With GFM Inverters

Xiaorui Liu, Hui Li, 2023, IEEE Open Journal of Power Electronics.

Faster than real-time simulation: methods, tools, and applications

Charalambos Konstantinou, Ioannis Zografopoulos, Juan Ospina, 2021, MSCPES@CPSIoTWeek.

Is Homophily a Necessity for Graph Neural Networks?

Xiaorui Liu, Jiliang Tang, Neil Shah, 2021, International Conference on Learning Representations.

How does the Memorization of Neural Networks Impact Adversarial Robust Models?

Anil K. Jain, Xiaorui Liu, Wentao Wang, 2023, KDD.