Ninghao Liu

According to our database, Ninghao Liu authored at least 105 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Retrieval-Enhanced Knowledge Editing for Multi-Hop Question Answering in Language Models.

Yucheng Shi, Qiaoyu Tan, Xuansheng Wu, Shaochen Zhong, Kaixiong Zhou, Ninghao Liu

CoRR, 2024

Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era.

Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu

CoRR, 2024

A Survey of Deep Learning and Foundation Models for Time Series Forecasting.

John A. Miller, Mohammed Aldosari, Farah Saeed, Nasid Habib Barna, Subas Rana, Ismailcem Budak Arpinar, Ninghao Liu

CoRR, 2024

Revolutionizing Finance with LLMs: An Overview of Applications and Insights.

Huaqin Zhao, Zhengliang Liu, Zihao Wu, Yiwei Li, Tianze Yang, Peng Shu, Shaochen Xu, Haixing Dai, Lin Zhao, Gengchen Mai, Ninghao Liu, Tianming Liu

CoRR, 2024

Automated Natural Language Explanation of Deep Visual Neurons with Large Models (Student Abstract).

Chenxu Zhao, Wei Qian, Yucheng Shi, Mengdi Huai, Ninghao Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks (Student Abstract).

Zihan Guan, Mengxuan Hu, Zhongliang Zhou, Jielu Zhang, Sheng Li, Ninghao Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation.

Shuang Zhou, Xiao Huang, Ninghao Liu, Huachi Zhou, Fu-Lai Chung, Long-Kai Huang

IEEE Trans. Knowl. Data Eng., December, 2023

In-Processing Modeling Techniques for Machine Learning Fairness: A Survey.

Mingyang Wan, Daochen Zha, Ninghao Liu, Na Zou

ACM Trans. Knowl. Discov. Data, April, 2023

Did You Train on My Dataset? Towards Public Dataset Protection with CleanLabel Backdoor Watermarking.

Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu

SIGKDD Explor., 2023

On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications.

Chenjiao Tan, Qian Cao, Yiwei Li, Jielu Zhang, Xiao Yang, Huaqin Zhao, Zihao Wu, Zhengliang Liu, Hao Yang, Nemin Wu, Tao Tang, Xinyue Ye, Lilong Chai, Ninghao Liu, Changying Li, Lan Mu, Tianming Liu, Gengchen Mai

CoRR, 2023

PokeMQA: Programmable knowledge editing for Multi-hop Question Answering.

Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang

CoRR, 2023

Applying Large Language Models and Chain-of-Thought for Automatic Scoring.

Gyeong-Geon Lee, Ehsan Latif, Xuansheng Wu, Ninghao Liu, Xiaoming Zhai

CoRR, 2023

Improving Faithfulness for Vision Transformers.

Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

CoRR, 2023

Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities.

Zhengliang Liu, Yiwei Li, Qian Cao, Junwen Chen, Tianze Yang, Zihao Wu, John Hale, John Gibbs, Khaled Rasheed, Ninghao Liu, Gengchen Mai, Tianming Liu

CoRR, 2023

A Theoretical Approach to Characterize the Accuracy-Fairness Trade-off Pareto Frontier.

Hua Tang, Lu Cheng, Ninghao Liu, Mengnan Du

CoRR, 2023

Automated Natural Language Explanation of Deep Visual Neurons with Large Models.

Chenxu Zhao, Wei Qian, Yucheng Shi, Mengdi Huai, Ninghao Liu

CoRR, 2023

From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning.

Xuansheng Wu, Wenlin Yao, Jianshu Chen, Xiaoman Pan, Xiaoyang Wang, Ninghao Liu, Dong Yu

CoRR, 2023

MedEdit: Model Editing for Medical Question Answering with External Knowledge Bases.

Yucheng Shi, Shaochen Xu, Zhengliang Liu, Tianming Liu, Xiang Li, Ninghao Liu

CoRR, 2023

RadOnc-GPT: A Large Language Model for Radiation Oncology.

Zhengliang Liu, Peilong Wang, Yiwei Li, Jason Holmes, Peng Shu, Lian Zhang, Chenbin Liu, Ninghao Liu, Dajiang Zhu, Xiang Li, Quanzheng Li, Samir H. Patel, Terence T. Sio, Tianming Liu, Wei Liu

CoRR, 2023

Mitigating Shortcuts in Language Models with Soft Label Encoding.

Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du

CoRR, 2023

Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges.

Fei Dou, Jin Ye, Geng Yuan, Qin Lu, Wei Niu, Haijian Sun, Le Guan, Guoyu Lu, Gengchen Mai, Ninghao Liu, Jin Lu, Zhengliang Liu, Zihao Wu, Chenjiao Tan, Shaochen Xu, Xianqiao Wang, Guoming Li, Lilong Chai, Sheng Li, Jin Sun, Hongyue Sun, Yunli Shao, Changying Li, Tianming Liu, Wenzhan Song

CoRR, 2023

Explainability for Large Language Models: A Survey.

Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du

CoRR, 2023

CohortGPT: An Enhanced GPT for Participant Recruitment in Clinical Study.

Zihan Guan, Zihao Wu, Zhengliang Liu, Dufan Wu, Hui Ren, Quanzheng Li, Xiang Li, Ninghao Liu

CoRR, 2023

Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification.

Haixing Dai, Lu Zhang, Lin Zhao, Zihao Wu, Zhengliang Liu, David Liu, Xiaowei Yu, Yanjun Lyu, Changying Li, Ninghao Liu, Tianming Liu, Dajiang Zhu

CoRR, 2023

Towards Personalized Cold-Start Recommendation with Prompts.

Xuansheng Wu, Huachi Zhou, Wenlin Yao, Xiao Huang, Ninghao Liu

CoRR, 2023

Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications.

Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, Sheng Li

CoRR, 2023

Efficient GNN Explanation via Learning Removal-based Attribution.

Yao Rong, Guanchu Wang, Qizhang Feng, Ninghao Liu, Zirui Liu, Enkelejda Kasneci, Xia Ben Hu

CoRR, 2023

Interpretation of Time-Series Deep Models: A Survey.

Ziqi Zhao, Yucheng Shi, Shushan Wu, Fan Yang, Wenzhan Song, Ninghao Liu

CoRR, 2023

BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks.

Zihan Guan, Mengxuan Hu, Zhongliang Zhou, Jielu Zhang, Sheng Li, Ninghao Liu

CoRR, 2023

Artificial General Intelligence (AGI) for Education.

Ehsan Latif, Gengchen Mai, Matthew Nyaaba, Xuansheng Wu, Ninghao Liu, Guoyu Lu, Sheng Li, Tianming Liu, Xiaoming Zhai

CoRR, 2023

Interactive System-wise Anomaly Detection.

Guanchu Wang, Ninghao Liu, Daochen Zha, Xia Ben Hu

CoRR, 2023

On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence.

Gengchen Mai, Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao

CoRR, 2023

AGI for Agriculture.

Guoyu Lu, Sheng Li, Gengchen Mai, Jin Sun, Dajiang Zhu, Lilong Chai, Haijian Sun, Xianqiao Wang, Haixing Dai, Ninghao Liu, Rui Xu, Daniel Petti, Changying Li, Tianming Liu

CoRR, 2023

Black-box Backdoor Defense via Zero-shot Image Purification.

Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Ninghao Liu

CoRR, 2023

Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking.

Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu

CoRR, 2023

A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges.

Xuansheng Wu, Kaixiong Zhou, Mingchen Sun, Xin Wang, Ninghao Liu

CoRR, 2023

ChatAug: Leveraging ChatGPT for Text Data Augmentation.

Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Zihao Wu, Lin Zhao, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Quanzheng Li, Dinggang Shen, Tianming Liu, Xiang Li

CoRR, 2023

NoPPA: Non-Parametric Pairwise Attention Random Walk Model for Sentence Representation.

Xuansheng Wu, Zhiyi Zhao, Ninghao Liu

CoRR, 2023

Matching Exemplar as Next Sentence Prediction (MeNSP): Zero-shot Prompt Learning for Automatic Scoring in Science Education.

Xuansheng Wu, Xinyu He, Tianming Li, Ninghao Liu, Xiaoming Zhai

CoRR, 2023

Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection.

Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking.

Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

International Workshop on Learning with Knowledge Graphs: Construction, Embedding, and Reasoning.

Qing Li, Xiao Huang, Ninghao Liu, Yuxiao Dong, Guansong Pang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Adaptive Label Smoothing To Regularize Large-Scale Graph Training.

Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Mitigating Algorithmic Bias with Limited Annotations.

Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning.

Yucheng Shi, Kaixiong Zhou, Ninghao Liu

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Black-box Backdoor Defense via Zero-shot Image Purification.

Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Jin Sun, Ninghao Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DIVISION: Memory Efficient Training via Dual Activation Precision.

Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu

Proceedings of the International Conference on Machine Learning, 2023

Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation.

Qiaoyu Tan, Daochen Zha, Ninghao Liu, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu

Proceedings of the IEEE International Conference on Data Mining, 2023

XGBD: Explanation-Guided Graph Backdoor Detection.

Zihan Guan, Mengnan Du, Ninghao Liu

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Knowledge Enhanced Deep Learning: Application to Pandemic Prediction.

John A. Miller, Nasid Habib Barna, Subas Rana, Ismailcem Budak Arpinar, Ninghao Liu

Proceedings of the 9th IEEE International Conference on Collaboration and Internet Computing, 2023

Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision.

Feng Luo, Ling Liu, G. Geoff Wang, Vijay Kumar, Mark S. Ashton, Jacob D. Abernethy, Fatemeh Afghah, Matthew H. E. M. Browning, David Coyle, Philip M. Dames, Tom O'Halloran, James Hays, Patrick Heisl, Chenfanfu Jiang, Puskar Khanal, Venkat Narayan Krovi, Sara Kuebbing, Nianyi Li, JingJing Liang, Ninghao Liu, Steve McNulty, Christopher M. Oswalt, Neil Pederson, Demetri Terzopoulos, Christopher W. Woodall, Yongkai Wu, Jian Yang, Yin Yang, Liang Zhao

Proceedings of the 5th IEEE International Conference on Cognitive Machine Intelligence, 2023

GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction.

Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks.

Zihan Guan, Lichao Sun, Mengnan Du, Ninghao Liu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training.

Wenxiong Liao, Zhengliang Liu, Yiyang Zhang, Xiaoke Huang, Fei Qi, Siqi Ding, Hui Ren, Zihao Wu, Haixing Dai, Sheng Li, Lingfei Wu, Ninghao Liu, Quanzheng Li, Tianming Liu, Xiang Li, Hongmin Cai

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Matching Exemplar as Next Sentence Prediction (MeNSP): Zero-Shot Prompt Learning for Automatic Scoring in Science Education.

Xuansheng Wu, Xinyu He, Tianming Liu, Ninghao Liu, Xiaoming Zhai

Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

SEAT: Stable and Explainable Attention.

Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution.

Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Differentiated Explanation of Deep Neural Networks With Skewed Distributions.

Weijie Fu, Meng Wang, Mengnan Du, Ninghao Liu, Shijie Hao, Xia Hu

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Defense Against Explanation Manipulation.

Ruixiang Tang, Ninghao Liu, Fan Yang, Na Zou, Xia Hu

Frontiers Big Data, 2022

Towards Memory Efficient Training via Dual Activation Precision.

Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu

CoRR, 2022

MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs.

Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen, Soo-Hyun Choi, Xia Hu

CoRR, 2022

Geometric Graph Representation Learning via Maximizing Rate Reduction.

Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks.

Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning.

Shuang Zhou, Xiao Huang, Ninghao Liu, Qiaoyu Tan, Fu-Lai Chung

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Data Science and Artificial Intelligence for Responsible Recommendations.

Shoujin Wang, Ninghao Liu, Xiuzhen Zhang, Yan Wang, Francesco Ricci, Bamshad Mobasher

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks.

Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

G-Mixup: Graph Data Augmentation for Graph Classification.

Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu

Proceedings of the International Conference on Machine Learning, 2022

DEGREE: Decomposition Based Explanation for Graph Neural Networks.

Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu

Proceedings of the Tenth International Conference on Learning Representations, 2022

AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training.

Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Tutorial on Deep Learning Interpretation: A Data Perspective.

Zhou Yang, Ninghao Liu, Xia Ben Hu, Fang Jin

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation.

Fan Yang, Ninghao Liu, Mengnan Du, Xia Hu

SIGKDD Explor., 2021

Adversarial Attacks and Defenses: An Interpretation Perspective.

Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu

SIGKDD Explor., 2021

Learning credible DNNs via incorporating prior knowledge and model local explanation.

Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu

Knowl. Inf. Syst., 2021

Modeling Techniques for Machine Learning Fairness: A Survey.

Mingyang Wan, Daochen Zha, Ninghao Liu, Na Zou

CoRR, 2021

ExAD: An Ensemble Approach for Explanation-based Adversarial Detection.

Raj Vardhan, Ninghao Liu, Phakpoom Chinprutthiwong, Weijie Fu, Zhenyu Hu, Xia Ben Hu, Guofei Gu

CoRR, 2021

Sparse-Interest Network for Sequential Recommendation.

Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao, Ninghao Liu, Jingren Zhou, Hongxia Yang, Xia Hu

Proceedings of the WSDM '21, 2021

Dynamic Memory based Attention Network for Sequential Recommendation.

Qiaoyu Tan, Jianwei Zhang, Ninghao Liu, Xiao Huang, Hongxia Yang, Jingren Zhou, Xia Hu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter.

Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu

BMC Medical Informatics Decis. Mak., 2020

Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability.

Ninghao Liu, Yunsong Meng, Xia Hu, Tie Wang, Bo Long

CoRR, 2020

Adversarial Machine Learning: An Interpretation Perspective.

Ninghao Liu, Mengnan Du, Xia Hu

CoRR, 2020

Techniques for interpretable machine learning.

Mengnan Du, Ninghao Liu, Xia Hu

Commun. ACM, 2020

Learning to Hash with Graph Neural Networks for Recommender Systems.

Qiaoyu Tan, Ninghao Liu, Xing Zhao, Hongxia Yang, Jingren Zhou, Xia Hu

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Deep Neural Networks with Knowledge Instillation.

Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Learning sparse codes from compressed representations with biologically plausible local wiring constraints.

Kion Fallah, Adam Willats, Ninghao Liu, Christopher Rozell

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks.

Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Explainable Recommender Systems via Resolving Learning Representations.

Ninghao Liu, Yong Ge, Li Li, Xia Hu, Rui Chen, Soo-Hyun Choi

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Deep Representation Learning for Social Network Analysis.

Qiaoyu Tan, Ninghao Liu, Xia Hu

Frontiers Big Data, 2019

On Attribution of Recurrent Neural Network Predictions via Additive Decomposition.

Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu

Proceedings of the World Wide Web Conference, 2019

Representation Interpretation with Spatial Encoding and Multimodal Analytics.

Ninghao Liu, Mengnan Du, Xia Hu

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Using Deep Neural Network to Identify Cancer Survivors Living with Post-Traumatic Stress Disorder on Social Media.

Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu

Proceedings of the 4th International Workshop on Semantics-Powered Data Mining and Analytics co-located with the 18th International Semantic Web Conference (ISWC 2019), 2019

An Interpretable Neural Model with Interactive Stepwise Influence.

Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Identification of Cancer Survivors Living with PTSD on Social Media.

Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu

Proceedings of the MEDINFO 2019: Health and Wellbeing e-Networks for All, 2019

Is a Single Vector Enough?: Exploring Node Polysemy for Network Embedding.

Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, Xia Hu

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Structured Cross-Modal Anomaly Detection.

Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu

Proceedings of the International Joint Conference on Neural Networks, 2019

Learning Credible Deep Neural Networks with Rationale Regularization.

Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

Spam Detection on Social Networks.

Ninghao Liu, Xia Hu

Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Adversarial Detection with Model Interpretation.

Ninghao Liu, Hongxia Yang, Xia Hu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

On Interpretation of Network Embedding via Taxonomy Induction.

Ninghao Liu, Xiao Huang, Jundong Li, Xia Hu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Towards Explanation of DNN-based Prediction with Guided Feature Inversion.

Mengnan Du, Ninghao Liu, Qingquan Song, Xia Hu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Contextual Outlier Interpretation.

Ninghao Liu, Donghwa Shin, Xia Hu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Towards Interpretation of Recommender Systems with Sorted Explanation Paths.

Fan Yang, Ninghao Liu, Suhang Wang, Xia Hu

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Accelerated Local Anomaly Detection via Resolving Attributed Networks.

Ninghao Liu, Xiao Huang, Xia Hu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Machine learning to predict rapid progression of carotid atherosclerosis in patients with impaired glucose tolerance.

Xia Hu, Peter D. Reaven, Aramesh Saremi, Ninghao Liu, Mohammad Ali Abbasi, Huan Liu, Raymond Q. Migrino

EURASIP J. Bioinform. Syst. Biol., 2016

2014

Distance-weighted backlog differentials for back-pressure routing in multi-hop wireless networks.

Jing Lu, Zuming Huang, Ninghao Liu, Quansheng Guan

Proceedings of the 2014 IEEE/CIC International Conference on Communications in China, 2014

2013

A Node Deployment Algorithm Based on Van Der Waals Force in Wireless Sensor Networks.

Xiangyu Yu, Ninghao Liu, Weipeng Huang, Xin Qian, Tao Zhang

Int. J. Distributed Sens. Networks, 2013