Preprint
[1] Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models
preprint, 2024
[2] Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations
preprint, 2024
[3] Jie Ren*, Kangrui Chen*, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models
preprint, 2024
[4] Shenglai Zeng, Jiankun Zhang, Bingheng Li, Yuping Lin, Tianqi Zheng, Dante Everaert, Hanqing Lu, Hui Liu, Hui Liu, Yue Xing, Monica Xiao Cheng, Jiliang Tang
Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective
preprint, 2024
[5] Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
preprint, 2024
[6] Pengfei He, Zitao Li, Yue Xing, Yaling Li, Jiliang Tang, Bolin Ding
Make LLMs Better Zero-Shot Reasoners: Structure-Oriented Autonomous Reasoning
preprint, 2024
[7] Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing
Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study
Presented at the Workshops on M3L & SFLLM, 38th Conference on Neural Information Processing Systems (NeurIPS), 2024
[8] Xinnan Dai, Haohao Qu, Yifen Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
preprint, 2024
[9] Xinnan Dai, Qihao Wen, Yifei Shen, Hongzhi Wen, Dongsheng Li, Jiliang Tang, Caihua Shan
Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path
preprint, 2024
[10] Guangliang Liu*, Haitao Mao*, Bochuan Cao, Zhiyu Xue, Kristen Johnson, Jiliang Tang, Rongrong Wang
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept
preprint, 2024
[11] Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li
Graph Machine Learning in the Era of Large Language Models (LLMs)
preprint, 2024
[12] Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
preprint, 2024
[13] Harry Shomer, Jay Revolinsky, Jiliang Tang
Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
preprint, 2024
[14] Jay Revolinsky*, Harry Shomer*, Jiliang Tang
Understanding the Generalizability of Link Predictors Under Distribution Shifts on Graphs
preprint, 2024
[15] Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang
Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models
preprint, 2024
[16] Qiaolin Lu*, Jiayuan Ding*, Lingxiao Li, Yi Chang, Jiliang Tang, Xiaojie Qiu
Graph Contrastive Learning of Subcellular-resolution Spatial Transcriptomics Improves Cell Type Annotation and Reveals Critical Molecular Pathways
preprint, 2024
[17] Kaiwen Dong, Haitao Mao, Zhichun Guo, Nitesh V Chawla
Universal link predictor by In-context Learning
preprint, 2024
[18] Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang
A Data Generation Perspective to the Mechanism of In-Context Learning
preprint, 2024
[19] Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang
Copyright Protection in Generative AI: A Technical Perspective
preprint, 2024
[20] Wenzhuo Tang*, Renming Liu*, Hongzhi Wen, Xinnan Dai, Jiayuan Ding, Hang Li, Wenqi Fan, Yuying Xie, Jiliang Tang
A General Single-Cell Analysis Framework via Conditional Diffusion Generative Models
preprint, 2023
[21] Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Lingjuan Lyu, Wenqi Fan, Hui Liu, Jiliang Tang
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models
preprint, 2023
[22] Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang
Towards Generating Adversarial Examples on Mixed-type Data
preprint, 2022
[23] Wenqi Fan, Xiangyu Zhao, Xiao Chen, Jingran Su, Jingtong Gao, Lin Wang, Qidong Liu, Yiqi Wang, Han Xu, Lei Chen, Qing Li
A Comprehensive Survey on Trustworthy Recommender Systems
preprint, 2022
[24] Yaxin Li, Xiaorui Liu, Han Xu, Wentao Wang, Jiliang Tang
Enhancing Adversarial Training with Feature Separability
preprint, 2022
Publications in 2024
[1] Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
Towards Neural Scaling Laws on Graphs
In Proceedings of the 3rd Learning on Graphs Conference (LoG), 2024
[2] Hang Li, Wei Jin, Geri Skenderi, Harry Shomer, Wenzhuo Tang, Wenqi Fan, Jiliang Tang
Sub-graph Based Diffusion Model for Link Prediction
In Proceedings of the 3rd Learning on Graphs Conference (LoG), 2024
[3] Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
A Pure Transformer Pretraining Framework on Text-attributed Graphs
In Proceedings of the 3rd Learning on Graphs Conference (LoG), 2024
[4] Pengfei He, Yue Xing, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou
Stealthy Backdoor Attack via Confidence-driven Sampling
In Transactions on Machine Learning Research (TMLR), 2024
[5] Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS, Datasets and Benchmarks track), 2024
[6] Li Ma*, Haoyu Han*, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang
Mixture of Link Predictors
In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS), 2024
[7] Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Marie Johnson
Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
[8] Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, Jiliang Tang
On the Generalization of Training-based ChatGPT Detection Methods
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
[9] Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang
Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
[10] Kaiqi Yang, Hang Li, Hongzhi Wen, Tai-Quan Peng, Jiliang Tang, Hui Liu
Are Large Language Models (LLMs) Good Social Predictors?
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
[11] Jiayuan Ding, Lingxiao Li, Qiaolin Lu, Julian Venegas, Yixin Wang, Lidan Wu, Wei Jin, Hongzhi Wen, Renming Liu, Wenzhuo Tang, Xinnan Dai, Zhaoheng Li, Wangyang Zuo, Yi Chang, Yu Leo Lei, Lulu Shang, Patrick Danaher, Yuying Xie, Jiliang Tang
SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology
Journal of Computational Biology, Vol. 31, No. 9, 2024
[12] Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu
Spectral-Aware Augmentation for Enhanced Graph Representation Learning
In Proceedings of the 33rd ACM International on Conference on Information and Knowledge Management (CIKM), 2024
[13] Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective
In Proceedings of 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
[14] Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
LPFormer: An Adaptive Graph Transformer for Link Prediction
In Proceedings of 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
[15] Xiaowei Qian*, Zhimeng Guo*, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark
In Proceedings of 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
[16] Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang
Source Free Graph Unsupervised Domain Adaptation
In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM), 2024
[17] Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
In Proceedings of the 18th European Conference on Computer Vision (ECCV), 2024
[18] Shenglai Zeng*, Yaxin Li*, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin
Exploring Memorization in Fine-tuned Language Models
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), 2024
[19] Shenglai Zeng*, Jiankun Zhang*, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), 2024
[20] Bingheng Li*, Linxin Yang*, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
[21] Haitao Mao*, Zhikai Chen*, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
Position Paper: Graph Foundation Models
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
[22] Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
[23] Lichao Sun, Yue Huang, Haoran Wang, et al.
Position Paper: TrustLLM: Trustworthiness in Large Language Models
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
[24] Huimin Zou, Jiquan Chen, Xianglan Li, Michael Abraha, Xiangyu Zhao, Jiliang Tang
Modeling Net Ecosystem Exchange of CO2 with Gated Recurrent Unit Neural Networks
In Agricultural and Forest Meteorology, 2024
[25] Jiayuan Ding*, Renming Liu*, Hongzhi Wen*, Wenzhuo Tang*, Zhaoheng Li, Julian Venegas, Runze Su, Dylan Molho, Wei Jin, Yixin Wang, Qiaolin Lu, Lingxiao Li, Wangyang Zuo, Yi Chang, Yuying Xie, Jiliang Tang
DANCE: a deep learning library and benchmark platform for single-cell analysis
In Genome Biology, 2024
[26] Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu
Content Knowledge Identification with Multi-Agent Large Language Models (LLMs)
In Proceedings of the 25th International Conference on Artificial Intelligence in Education (AIED), 2024
[27] Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, Jiliang Tang
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024
[28] Ziwen Zhao, Yuhua Li, Yixiong Zou, Jiliang Tang, Ruixuan Li
Masked Graph Autoencoder with Non-discrete Bandwidths
In Proceedings of the ACM Web Conference (WWW), 2024
[29] Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin
Whole Page Unbiased Learning to Rank
In Proceedings of the ACM Web Conference (WWW), 2024
[30] Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Revisiting Link Prediction: a Data Perspective
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
[31] Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Label-free Node Classification on Graphs with Large Language Models (LLMs)
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
[32] Hongzhi Wen*, Wenzhuo Tang*, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
CellPLM: Pre-training of Cell Language Model Beyond Single Cells
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
[33] Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang
Sharpness-Aware Data Poisoning Attack
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024 (spotlight: 5%)
[34] Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada
Structural Fairness-aware Active Learning for Graph Neural Networks
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
[35] Yaxin Li*, Jie Ren*, Han Xu, Hui Liu
Neural Style Protection: Counteracting Unauthorized Neural Style Transfer
Winter Conference on Applications of Computer Vision (WACV) 2024
Publications in 2023
[1] Yingqian Cui*, Jie Ren*, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Yue Xing, Jiliang Tang
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
NeurIPS 2023 Workshop on Diffusion Models
[2] Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
In ACM SIGKDD Explorations Newsletter (SIGKDD Explorations), 2023
[3] Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang
Distance-Based Propagation for Efficient Knowledge Graph Reasoning
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
[4] Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang
Towards Label Position Bias in Graph Neural Networks
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
[5] Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
[6] Juanhui Li*, Harry Shomer*, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
[7] Wei Jin*, Haitao Mao*, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
[8] Zitao Liu, Qiongqiong Liu, Teng Guo, Jiahao Chen, Shuyan Huang, Xiangyu Zhao, Jiliang Tang, Weiqi Luo, Jian Weng
XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
[9] Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu
Learning Representations for Hyper-Relational Knowledge Graphs
In Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2023
[10] Wentao Wang, Harry Shomer, Yuxuan Wan, Yaxin Li, Jiangtao Huang and Hui Liu
A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data
In Proceedings of the 32nd ACM International on Conference on Information and Knowledge Management (CIKM), 2023
[11] Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
Single-Cell Multimodal Prediction via Transformers
In Proceedings of 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023
[12] Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu
Enhancing Graph Representations Learning with Decorrelated Propagation
In Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
[13] Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil K. Jain, Jiliang Tang
How does the Memorization of Neural Networks Impact Adversarial Robust Models?
In Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
[14] Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023
[15] Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang
Alternately Optimized Graph Neural Networks
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
[16] Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
[17] Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang
Probabilistic Categorical Adversarial Attack and Adversarial Training
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
[18] Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, and Jiliang Tang
Adversarial Attacks for Black-box Recommender Systems via Copying Transferable Cross-domain User Profiles
In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023
[19] Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li
Generative Diffusion Models on Graphs: Methods and Applications
In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023
[20] Jamell Dacon and Jiliang Tang
Beyond Race and Gender: A Look at Sociodemographic Biases Toward Persons with Disabilities
In Proceedings in the 9th International Conference on Computational Social Science, 2023
[21] Jamell Dacon and Jiliang Tang
Can We Identify and Dismantle ISMs that Plague Our Society: An Online Approach
In Proceedings in the 9th International Conference on Computational Social Science, 2023
[22] Juanhui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin
Graph Enhanced BERT for Query Understanding
In Proceedings of 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
[23] Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
Toward Degree Bias in Embedding-Based Knowledge Graph Completion
In Proceedings of the ACM Web Conference (WWW), 2023
[24] Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
Empowering Graph Representation Learning with Test-Time Graph Transformation
In Proceedings of International Conference on LearningRepresentations (ICLR), 2023
[25] Jie Ren*, Han Xu*, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang
Transferable Unlearnable Examples
In Proceedings of International Conference on LearningRepresentations (ICLR), 2023
Publications in 2022
[1] Pengfei He, Haochen Liu, Xiangyu Zhao, Hui Liu, Jiliang Tang
PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations
In Proceedings of the 31st ACM International on Conference on Information and Knowledge Management (CIKM), 2022
[2] Haitao Mao*, Lixin Zou*, Xiaokai Chu, Jiliang Tang, Shuaiqiang Wang, Wenwen ye, Dawei yin
A Large Scale Search Dataset for Unbiased Learning to Rank
In Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), 2022
[3] Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang
Imbalanced Adversarial Training with Reweighting
In Proceedings of the 2022 IEEE International Conference on Data Mining, 2022
[4] Jamell Dacon, Haochen Liu and Jiliang Tang
Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference
In Proceedings in the 29th International Conference on Computational Linguistics, 2022
[5] Jamell Dacon, Harry Shomer, Shaylynn Crum-Dacon, Jiliang Tang
Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals
In Proceedings of the Queer in AI Workshop at NAACL, 2022
[6] Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering
In ACM Transactions on Information Systems (TOIS), 2022
[7] Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Ying Bin
Condensing Graphs via One-Step Gradient Matching
In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022
[8] Wei Jin*, Xiaorui Liu*, Yao Ma, Charu Aggarwal, Jiliang Tang
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022
[9] Hongzhi Wen*, Jiayuan Ding*, Wei Jin*, Yuying Xie, Jiliang Tang
Graph Neural Networks for Multimodal Single-Cell Data Integration
In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022
[10] Jamell Dacon
Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English
In Proceedings of the Second Workshop on Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP) at NAACL, 2022
[11] Haochen Liu*, Yiqi Wang*, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Yunhao Liu, Anil K. Jain and Jiliang Tang
Trustworthy AI: A Computational Perspective
In ACM Transactions on Intelligent Systems and Technology (TIST), 2022
[12] Jamell Dacon, Haochen Liu and Jiliang Tang
Using Inference to Mitigate Linguistic Bias Against African American English
In Proceedings of the 8th International Conference on Computational Social Science (IC2S2), 2022
[13] Jamell Dacon and Jiliang Tang
Examining Word Representations between #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020
In Proceedings of the 8th International Conference on Computational Social Science (IC2S2), 2022
[14] Jamell Dacon
Understanding African American English on a Token-Level Beyond Accuracy
In Proceedings of the 8th International Conference on Computational Social Science (IC2S2), 2022
[15] Wenqi Fan*, Xiaorui Liu*, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
Graph Trend Filtering Networks for Recommendation
In Proceedings of 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022
[16] Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu and Jiliang Tang
Toward Annotator Group Bias in Crowdsourcing
In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL), 2022
[17] Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang and Neil Shah
Graph Condensation for Graph Neural Networks
In Proceedings of International Conference on LearningRepresentations (ICLR), 2022
[18] Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah and Jiliang Tang
Automated Self-Supervised Learning for Graphs
In Proceedings of International Conference on Learning Representations (ICLR), 2022
[19] Yao Ma, Xiaorui Liu, Neil Shah and Jiliang Tang
Is Homophily a Necessity for Graph Neural Networks
In Proceedings of International Conference on Learning Representations (ICLR), 2022
[20] Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Hui Liu, Jiliang Tang and Youlong Cheng
Rating Distribution Calibration for Selection Bias Mitigation in Recommendations
In Proceedings of the 31st Web Conference (WWW), 2022
[21] Wentao Wang, Joseph Thekinen, Xiaorui Liu, Zitao Liu and Jiliang Tang
Learning from Imbalanced Crowdsourced Labeled Data
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022
[22] Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie and Jiliang Tang
Localized Graph Collaborative Filtering
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022
[23] Xiangyu Zhao, Wenqi Fan, Hui Liu and Jiliang Tang
Multi-type Urban Crime Prediction
In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022
Publications in 2021
[1] Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu and Jiliang Tang
Graph Neural Networks with Adaptive Residual
In Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS), 2021
[2] Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Xudong Zheng, Xiaobing Liu and Xiwang Yang
AdaED: Adaptive Embedding Dimension for Online Recommender Systems
In Proceedings of the 21st IEEE International Conference on Data Mining (ICDM), 2021
[3] Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang and Neil Shah
A Unified View on Graph Neural Networks as Graph Signal Denoising
In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021
[4] Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu and Jiliang Tang
Deep Adversarial Network Alignment
In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021
[5] Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu Aggarwal and Jiliang Tang
Graph Feature Gating Networks
In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021
[6] Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Jiliang Tang and Youlong Cheng
Self-supervised Learning for Alleviating Selection Bias in Recommendation Systems
In International Workshop on Industrial Recommendation Systems (IRS) at SIGKDD, 2021
[7] Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen and Jiliang Tang
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
[8] Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang and Chong Wang
Automated Loss Function Search in Recommendations
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
[9] Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu and Jiliang Tang
Graph Adversarial Attack via Rewiring
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
[10] Jamell Dacon and Haochen Liu
Does Gender Matter in the News? Detecting and Examining Gender Bias in News Articles
In Proceedings of the 7th International Conference on Computational Social Science (IC2S2), 2021
[11] Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan and Jiliang Tang
Elastic Graph Neural Networks
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
[12] Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain and Jiliang Tang
To be Robust or to be Fair: Towards Fairness in Adversarial Training
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
[13] Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu and Jiliang Tang
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL), Findings of ACL, 2021
[14] Xiangyu Zhao, Long Xia, Lixin Zou, Dawei Yin, Hui Liu and Jiliang Tang
User Simulation via Supervised Generative Adversarial Network
In Proceedings of the 30th Web Conference (WWW), 2021
[15] Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao and Bo Long
Field-aware Embedding Space Searching in Recommender Systems
In Proceedings of the 30th Web Conference (WWW), 2021
[16] Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang and Ming Yan
Linear Convergent Decentralized Optimization with Compression
In Proceedings of the 9th International Conference on Learning Representations (ICLR), 2021
[17] Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu and Jiliang Tang
Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2021
[18] Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Hui Liu and Jiliang Tang
Online Advertising Impression Strategy in Recommender Systems
In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021
[19] Yaxin Li, Wei Jin, Han Xu and Jiliang Tang
DeepRobust: A Platform for Adversarial Attacks and Defenses
In Demonstrations Program of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021
[20] Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu and Jiliang Tang
Node Similarity Preserving Graph Convolutional Networks
In Proceedings of the 14th ACM Conference on Web Search and Data Mining (WSDM), 2021
[21] Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang and Qing Li
CopyAttack: Attacking Black-box Recommendations via Copying Cross-domain User Profiles
In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021
Publications in 2020
[1] Wei Jin, Yaxin Li, Han Xu, Yiqi Wang and Jiliang Tang
Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study
[Repository Code]
In ACM SIGKDD Explorations Newsletter (SIGKDD Explorations), 2020
[2] Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang and Neil Shah
A Unified View on Graph Neural Networks as Graph Signal Denoising
preprint, 2020
[3] Aaron Brookhouse*, Tyler Derr*, Hamid Karimi*, H. Russell Bernard and Jiliang Tang
Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries
preprint, 2020
[4] Haochen Liu, Zitao Liu, Zhongqin Wu and Jiliang Tang
Personalized Multimodal Feedback Generation in Education
In Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020
[5] Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu and Jiliang Tang
Does Gender Matter? Towards Fairness in Dialogue Systems
In Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020
[6] Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu and Jiliang Tang
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
[7] Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank and Jiliang Tang
Understanding and Promoting Teacher Connections in Online Social Media: A Case Study on Pinterest
In Proceedings of the 2020 IEEE International Conference on Engineering, Technology and Education (TALE), 2020
[8] Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu and Jiliang Tang
Learning from Incomplete Labeled Data via Adversarial Data Generation
In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020
[9] Juanhui Li*, Yao Ma*, Yiqi Wang, Charu Aggarwal, Chang-Dong Wang, Jiliang Tang
Graph Pooling with Representativeness
In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020
[10] Wentao Wang, Guowei Xu, Wenbiao Ding, Gale Yan Huang, Guoliang Li, Jiliang Tang and Zitao Liu
Representation Learning from Limited Educational Data with Crowdsourced Labels
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
[11] Wenqi Fan, Yao Ma , Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang and Dawei Yin
A Graph Neural Network Framework for Social Recommendations
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
[12] Xiangyu Zhao, Long Xia, Lixin Zou, Dawei Yin, Hui Liu and Jiliang Tang
Whole-Chain Recommendations
In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020
[13] Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu and Jiliang Tang
Self-supervised Learning on Graphs: Deep Insights and New Direction
preprint, 2020
[14] Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang and Qing Li
Attacking Black-box Recommendations via Copying Cross-domain User Profiles
preprint, 2020
[15] Haochen Liu, Zhiwei Wang, Tyler Derr and Jiliang Tang
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue Models
preprint, 2020
[16] Yiqi Wang*, Yao Ma*, Charu Aggarwal and Jiliang Tang
Non-IID Graph Neural Networks
preprint, 2020
[17] Hao Yuan, Jiliang Tang, Xia Hu and Shuiwang Ji
XGNN: Towards Model-Level Explanations of Graph Neural Networks
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[18] Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang and Jiliang Tang
Graph Structure Learning for Robust Graph Neural Networks
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[19] Xiangyu Zhao, Xudong Zheng, Xiwang Yang, Xiaobing Liu and Jiliang Tang
Jointly Learning to Recommend and Advertise
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[20] Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
DeepRobust: A PyTorch Library for Adversarial Attacksand Defenses
preprint, 2020
[21] Haochen Liu*, Xiangyu Zhao*, Chong Wang, Xiaobing Liu and Jiliang Tang
Automated Embedding Size Search in Deep Recommender Systems
In Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020
[22] Yao Ma, Ziyi Guo, Zhaochun Ren, Jiliang Tang and Dawei Yin
Streaming Graph Neural Networks
In Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020
[23] Hamid Karimi*, Tyler Derr*, Jiangtao Huang and Jiliang Tang
Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network
In Proceedings of 13th International Conference on Educational Data Mining (EDM), 2020
[24] Hamid Karimi, Kaitlin T. Torphy, Tyler Derr, Kenneth A. Frank and Jiliang Tang
Characterizing Teacher Connections in Online Social Media: A Case Study on Pinterest
In proceedings of 2020 Annual ACM Conference on Learning at Scale, 2020
[25] Hang Li, Zhiwei Wang, Jiliang Tang, Wenbiao Ding and Zitao Liu
Siamese Neural Networks for Class Activity Detection
In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), 2020
[26] Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank and Jiliang Tang
Towards Improving Sample Representativeness of Teachers on Online Social Media: A Case Study on Pinterest
In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), 2020
[27] Gale Yan Huang, Jiahao Chen, Haochen Liu, Weiping Fu, Wenbiao Ding, Jiliang Tang, Songfan Yang and Zitao Liu
Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms
In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), 2020
[28] Tyler Derr, Zhiwei Wang, Jamell Dacon and Jiliang Tang.
Link and Interaction Polarity Predictions in Signed Networks
Social Network Analysis and Mining. 10(18). 2020
[29] Christina B.Azodi, Jiliang Tang and Shin-Han Shiu
Opening the Black Box: Interpretable Machine Learning for Geneticists
In Trends in Genetics, 2020
[30] Jie Zhuang, Tai-quan (Winson) Peng, Jiliang Tang and Yingcai Wu
Mixed and blended emotional reactions to 2014 Ebola outbreak
In Journal of Global Health, 2020
[31] Saket Sathe, Sayani Aggarwal and Jiliang Tang
Gene Expression and Protein Function: A Survey of Deep Learning Methods
In ACM SIGKDD Explorations, 2020
[32] Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan
A Double Residual Compression Algorithm for Efficient Distributed Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
[33] Xiangyu Zhao, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu and Jiliang Tang
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
preprint, 2020
[34] Xiangyu Zhao and Jiliang Tang
Exploring Spatio-Temporal and Cross-Type Correlations for Crime Prediction
preprint, 2020
[35] Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang and Jiliang Tang
Traffic Flow Prediction via Spatial Temporal Graph Neural Network
In Proceedings of the World Wide Web Conference (WWW), 2020
[36] Amin Javari, Tyler Derr, Pouya Esmailian, Jiliang Tang, Kevin Chen-Chuan Chang
ROSE: Role-based Signed Network Embedding
In Proceedings of the World Wide Web Conference (WWW), 2020
[37] Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li and Jiliang Tang
Deep Adversarial Canonical Correlation Analysis
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2020
[38] Wentao Wang, Suhang Wang, Wenqi Fan, Zitao Liu and Jiliang Tang
Global-and-Local Aware Data Generation for the Class Imbalance Problem
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2020
[39] Teng Guo, Feng Xia, Shihao Zhen, Xiaomei Bai, Dongyu Zhang, Zitao Liu and Jiliang Tang
Graduate Employment Prediction with Bias
In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020
[40] Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang and Zitao Liu
Learning Multi-level Dependencies for Robust Word Recognition
In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020
[41] Tyler Derr
Network Analysis with Negative Links
In Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2020
[42] Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu Aggarwal and Jiliang Tang
Epidemic Graph Convolutional Network
In Proceedings of the Thirteenth ACM International Conference on Web Search and Data Mining (WSDM), 2020
Publications in 2019
[1] Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang and Huan Liu
Understanding and Identifying Rhetorical Questions in Social Media
In ACM Transactions on Intelligent Systems and Technology (TIST), 2019
[2] Ghazaleh Beigi, Jiliang Tang and Huan Liu
Social Science-guided Feature Engineering: A Novel Approach to Signed Link Analysis
In ACM Transactions on Intelligent Systems and Technology (TIST), 2019
[3] Hamid Karimi, Tyler Derr and Jiliang Tang
Characterizing the Decision Boundary of Deep Neural Networks
preprint, 2019
[4] Zhiwei Wang, Yao Ma, Zitao Liu and Jiliang Tang
R-transformer: Recurrent neural network enhanced transformer
preprint, 2019
[5] Zhiwei Wang, Xiaorui Liu, Jiliang Tang and Dawei Yin
Weight Loss Prediction in Social-Temporal Context
In IEEE International Conference on Healthcare Informatics (ICHI), 2019
[6] Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang and Qing Li
Deep Adversarial Social Recommendation
In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI), 2019
[7] Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang and Qing Li
Deep Social Collaborative Filtering
In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys), 2019
[8] Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang and Anil Jain
Adversarial attacks and defenses in images, graphs and text: A review
In International Journal of Automation and Computing (IJAC), 2019
[9] Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu and Jiliang Tang
Does Gender Matter? Towards Fairness in Dialogue Systems
preprint, 2019
[10] Haochen Liu, Tyler Derr, Zitao Liu and Jiliang Tang
Say what I want: Towards the dark side of neural dialogue models
preprint, 2019
[11] Hamid Karimi, Tyler Derr, Aaron Brookhouse and Jiliang Tang
Multi-Factor Congressional Vote Prediction
In International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019
[12] Tyler Derr, Cassidy Johnson, Yi Chang and Jiliang Tang
Balance in Signed Bipartite Networks
In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019
[13] Yao Ma, Suhang Wang, Charu C. Aggarwal and Jiliang Tang
Graph Convolutional Networks with EigenPooling
In Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
[14] Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu and Jiliang Tang
Deep Adversarial Network Alignment
Preprint, 2019
[15] Xiangyu Zhao, Long Xia, Jiliang Tang and Dawei Yin
Deep Reinforcement Learning for Search, Recommendation and Online Advertising: A Survey
In ACM SIGWEB Newsletter (SIGWEB), 2019
[16] Hamid Karimi and Jiliang Tang
Learning Hierarchical Discourse-level Structure for Fake News Detection
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HTL), 2019
[17] Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang and Dawei Yin
Graph Neural Networks for Social Recommendation
In Proceedings of the Web Conference (WWW), 2019
[18] Tianqiao Liu, Zhiwei Wang , Jiliang Tang, Songfan Yang and Zitao Liu
Recommender Systems with Heterogeneous Side Information
In Proceedings of the 28th International Conference on World Wide Web (WWW), 2019
[19] Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin and Jiliang Tang
Multi-dimensional Graph Convolutional Networks
Proceedings of the Nineteenth SIAM International Conference on Data Mining (SDM), 2019
[20] Guowei Xu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Gale Yan Huang and Zitao Liu
Learning Effective Embeddings from Crowdsourced Labels: An Educational Case Study
In Proceedings of IEEE International Conference on Data Engineering (ICDE), 2019
Publications in 2018
[1] Tyler Derr and Jiliang Tang
Congressional Vote Analysis Using Signed Networks
In International Conference on Data Mining Workshops (ICDMW), 2018
[2] Zhiwei Wang, Yao Ma, Dawei Yin and Jiliang Tang
Linked Recurrent Neural Networks
Preprint, 2018
[3] Yao Ma, Ziyi Guo, Zhaochun Ren, Eric Zhao, Jiliang Tang, Dawei Yin
Streaming Graph Neural Networks
Preprint, 2018
[4] Hamid Karimi, Jiliang Tang and Yanen Li
Toward End-to-End Deception Detection in Videos
In Proceedings of the 5th IEEE International Conference on Big Data, 2018
[5] Tyler Derr, Yao Ma and Jiliang Tang
Signed Graph Convolutional Networks
IEEE International Conference on Data Mining (ICDM), 2018
[6] Tyler Derr, Charu Aggarwal and Jiliang Tang
Signed Network Modeling Based on Structural Balance Theory
Proceedings of the 2018 ACM on Conference on Information and Knowledge Management (CIKM), 2018
[7] Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin and Jiliang Tang
Deep Reinforcement Learning for Page-wise Recommendations
In Proceedings of the 12th ACM Recommender Systems Conference, 2018
[8] Tyler Derr, Chenxing Wang, Suhang Wang and Jiliang Tang
Relevance Measurements in Online Signed Social Networks
In ACM SIGKDD 14th International Workshop on Mining and Learning with Graphs (MLG), 2018
[9] Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang and Dawei Yin
Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning
In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
[10] Xiangyu Zhao, Jiliang Tang
Crime in Urban Areas: A Data Mining Perspective
ACM SIGKDD Explorations Newsletter, 2018
[11] Hamid Karimi
Interpretable Multimodal Deception Detection in Videos
Proceedings of the ACM International Conference on Multimodal Interaction, 2018
[12] Tyler Derr, Zhiwei Wang and Jiliang Tang
Opinions Power Opinions: Joint Link and Interaction Polarity Predictions in Signed Networks
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
[13] Yao Ma, Suhang Wang and Jiliang Tang
Local and Global Information Preserved Network Embedding
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
[14] Hamid Karimi, Courtland VanDam, Liyang Ye, Jiliang Tang
End-to-End Compromised Account Detection
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018 *Best Paper Award*
[15] Courtland VanDam, Pang-Ning Tan, Jiliang Tang and Hamid Karimi
CADET: A Multi-View Learning Framework for Compromised Account Detection on Twitter
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
[16] Hamid Karimi, Proteek Roy, Sari Saba-Sadiya, Jiliang Tang
Multi-Source Multi-Class Fake News Detection
Proceedings of the 27th International Conference on Computational Linguistics, 2018
[17] Yao Ma, Jiliang Tang and Charu Aggarwal
Feature Engineering for Data Streams
Feature Engineering for Machine Learning and Data Analytics (CRC Press), 2018
[18] Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin.
Multidimensional network embedding with hierarchical structures
Proceedings of the 11th ACM Conference on Web Search and Data Mining (WSDM) 2018
[19] Hongshen Chen, Zhaochun Ren, Jiliang Tang, Yihong Eric Zhao and Dawei Yin
Hierarchical Variational Memory Network for Dialogue Generation
In Proceedings of the 27th International Conference on World Wide Web (WWW), 2018
[20] Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang and Huan Liu
Understanding and Predicting Delay in Reciprocal Relations
In Proceedings of the 27th International Conference on World Wide Web (WWW), 2018
[21] Tian Xie, Chi-Yu Li, Guan-Hua Tu and Jiliang Tang
How Voice Service Threatens Cellular-connected IoT Devices in the Operational 4G LTE Networks
In IEEE ICC Communication and Information Systems Security Symposium, 2018
[22] Makoto Yamada, Jiliang Tang et al.
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
[23] Suhang Wang, Jiliang Tang, Yilin Wang and Huan Liu
Exploring Hierarchical Structures for Recommender Systems
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
[24] Hongshen Chen, Xiaorui Liu, Dawei Yin and Jiliang Tang.
A Survey on Dialogue Systems: Recent Advances and New Frontiers
SIGKDD Explorations, 2018
[25] Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu.
CrossFire: Cross Media Joint Friend and Item Recommendations
Proceedings of the 11th ACM Conference on Web Search and Data Mining (WSDM) 2018
[26] Meizi Zhou, Zhuoye Ding, Jiliang Tang, Dawei Yin.
Micro Behaviors: A New Perspective in E-commerce Recommender Systems
Proceedings of the 11th ACM Conference on Web Search and Data Mining (WSDM) 2018
[27] Zihan Wang, Ziheng Jiang, Zhaochun Ren, Jiliang Tang, Dawei Yin.
A Path-constrained Framework for Discriminating Substitutable and Complementary Products in E-commerce
In Proceedings of the 11th ACM Conference on Web Search and Data Mining (WSDM) 2018
[28] Yilin Wang, Suhang Wang, Guojun Qi, Jiliang Tang, Baoxin.
Weakly Supervised Facial Attribute Manipulation via Deep Adversarial Network
IEEE Winter Conf. on Applications of Computer Vision (WACV), 2018
Publications in 2017
[1] Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Dawei Yin, Yihong Zhao and Jiliang Tang
Deep Reinforcement Learning for List-wise Recommendations
Preprint, 2017
[2] Zhiwei Wang, Tyler Derr, Dawei Yin and Jiliang Tang.
Understanding and Predicting Weight Loss with Mobile Social Networking Data
Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
[3] Xiangyu Zhao, Dawei Yin and Jiliang Tang.
Modeling Temporal-Spatial Correlation for Crime Predictions
Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
[4] Suhang Wang, Charu Aggarwal, Jiliang Tang, Huan Liu.
Attributed Signed Network Embedding
Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
[5] Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang and Huan Liu.
Attributed Network Embedding for Learning in a Dynamic Environment
Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
[6] Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang and Huan Liu.
Feature Selection: A Data Perspective
ACM Computing Surveys (CSUR), 2017
[7] Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang and Huan Liu.
Fake News Detection on Social Media: A Data Mining Perspectives
SIGKDD Explorations, 2017
[8] Yang Li, Quan Pan, Tao Yang, Suhang Wang, Jiliang Tang and Erik Cambria.
Learning Word Representations for Sentiment Analysis
Cognitive Computation, 2017
[9] Courtland VanDam, Jiliang Tang and Pang-ning Tan.
Understanding Compromised Accounts on Twitter
IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2017
[10] Guo-Jun Qi, Jiliang Tang, Jingdong Wang and Jiebo Luo.
Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017
[11] Yuening Hu, Changsung Kang, Jiliang Tang, Dawei Yin and Yi Chang.
Large-scale Location Prediction for Web Pages
IEEE Trans on Knowledge and Data Engineering (TKDE), 2017
[12] Jundong Li, Jiliang Tang and Huan Liu.
Reconstruction-based Unsupervised Feature Selection: An Embedded Approach
Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017
[13] Suhas Ranganth, Suhang Wang, Xia Hu, Jiliang Tang and Huan Liu.
Facilitating Time Critical Information Seeking in Social Media
IEEE Trans on Knowledge and Data Engineering (TKDE), 2017
[14] Jundong Li, Jiliang Tang and Huan Liu.
Recent Advances in Feature Selection: A Data Perspective
Tutorial in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017
[15] Lin Chen, Jiliang Tang and Baoxin Li
Supervised Feature Selection for Multi-class Data
Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
[16] Suhang Wang, Yilin Wang, Jiliang Tang, Charu Aggarwal, Suhas Ranganath and Huan Liu
Exploiting Hierarchical Structures for Unsupervised Feature Selection
Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
[17] Suhang Wang, Jiliang Tang, Charu Aggarwal, Yi Chang and Huan Liu
Signed Network Embedding in Social Media
Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
[18] Yang Li, Suhang Wang, Quan Pan, Tao Yang and Jiliang Tang
Price Recommendation on Vacation Rental Websites
Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
[19] Yilin Wang, Jiliang Tang, Jundong Li, Baoxin Li, Yali Wan, Clayton Mellina, Neil O'Hare and Yi Chang
Understanding and Discovering Deliberate Self-harm Content in Social Media
Proceedings of International World Wide Web Conference (WWW), 2017
[20] Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark Hasegawa-Johnson and Thomas Huang
Streaming Recommender Systems
Proceedings of International World Wide Web Conference (WWW), 2017
[21] Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath and Huan Liu
What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation
Proceedings of International World Wide Web Conference (WWW), 2017
[22] Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani and Huan Liu
User Identity Linkage across Online Social Netwroks: A Review
In ACM SIGKDD Explorations, 2017
[23] Kewei Cheng, Jundong Li, Jiliang Tang and Huan Liu
Unsupervised Sentiment Analysis with Signed Social Networks
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017
[24] Yilin Wang, Suhang Wang, Jiliang Tang, Guojun Qi, Huan Liu and Baoxin Li
CLARE:A Joint Approach to Label Classification and Tag Recommendation
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017
[25] Lu Jiang, Yannis Kalantidis, Liangliang Cao, Sachin Farfade, Jiliang Tang and Alex Hauptmann
Delving Deep into Personal Photo and Video Search
In the 10th International Conference on Web Search and Data Mining (WSDM), 2017
Publications in 2016
[1] Huan Liu, Fred Morstatter, Jiliang Tang and Reza Zafarani
The good, the bad and the ugly: uncovering novel research opportunities in social media mining
In International Journal of Data Science and Analytics, 2016
[2] Yunlong He, Jiliang Tang, Hua Ouyang, Changsung Kang, Dawei Yin and Yi Chang.
Learning to Rewrite Queries
In Proceedings of 25th ACM Conference on Information and Knowledge Management (CIKM), 2016
[3] Suhang Wang, Jiliang Tang, Fred Morstatter and Huan Liu.
Paired Restricted Boltzmann Machine for Linked Data
In Proceedings of 25th ACM Conference on Information and Knowledge Management (CIKM), 2016
[4] Suhang Wang, Jiliang Tang, Charu Aggarwal and Huan Liu.
Linked Document Embedding for Classification
In Proceedings of 25th ACM Conference on Information and Knowledge Management (CIKM), 2016
[5] Jiliang Tang, Yi Chang, Charu Aggarwal and Huan Liu.
A Survey of Signed Network Mining in Social Media
To appear in ACM Computing Surveys
[6] Dawei Yin, Yuening Hu, Jiliang Tang, Tim Daly Jr., Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois and Yi Chang.
Ranking Relevance in Yahoo Search
In Proceedings of the 22nd annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016
[7] Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark Hasegawa-Johnson, Thomas S. Huang.
Positive-Unlabeled Learning in Streaming Networks
In Proceedings of the 22nd annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016
[8] Ruifang He, Yang Liu, Guangchuan Yu, Jiliang Tang, Qinghua Hu and Jianwu Dang
Twitter Summarization with Social-Temporal Context
to appear in World Wide Web Journal
[9] Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada and Yan Liu.
Timeline Summarization with Life Cycle Models from Social Media
Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016
[10] Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu and Baoxin Li.
PPP: Joint Pointwise and Pairwise Image Label Prediction
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
[11] Ruifang He, Jiliang Tang, Pinghua Gong, Qinghua Hu and Bo Wang.
Multi-document summarization via group sparse learning
Information Sciences, 2016
[12] Ghazaleh Beigi, Jiliang Tang and Huan Liu.
Signed Link Analysis in Social Media Networks
The 10th International AAAI Conference on Weblogs and Social Media (ICWSM), 2016
[13] Suhas Ranganth, Xia Hu, Jiliang Tang, Suhang Wang and Huan Liu.
Identifying Rhetorical Questions in Social Media
The 10th International AAAI Conference on Weblogs and Social Media (ICWSM), 2016
[14] Pritam Gundecha, Jiliang Tang, Xia Hu and Huan Liu.
Exploring Personal Attributes from Unprotected Interactions
The 10th International AAAI Conference on Weblogs and Social Media (ICWSM)， 2016
[15] Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang and Huan Liu
Feature Selection: A Data Perspective
scikit-feature (an open-source feature selection repository in Python)
[16] Jiliang Tang, Charu Aggarwal and Huan Liu.
Node Classification in Signed Social Networks
SIAM International Conference on Data Mining (SDM), 2016
[17] Ghazaleh Beigi, Jiliang Tang, Suhang Wang and Huan Liu.
Exploiting Emotional Information for Trust/Distrust Prediction
SIAM International Conference on Data Mining (SDM), 2016
[18] Jiliang Tang, Charu Aggarwal and Huan Liu.
Recommendations in Signed Social Networks
the 25nd International World Wide Web Conference (WWW), 2016
[19] Suhas Ranganath, Xia Hu, Jiliang Tang and Huan Liu.
Understanding and Identifying Advocates of Political Campaigns on Social Media
ACM International Conference on Web Search and Data Mining (WSDM), 2016
[20] Suhas Ranganath, Fred Morstatter, Xia Hu, Jiliang Tang, Suhang Wang and Huan Liu.
Predicting Online Protest Participation of Social Media Users
the AAAI Conference on Artificial Intelligence (AAAI), 2016
[21] Jiliang Tang, SuhangWang, Xia Hu, Dawei Yin, Yingzhou Bi, Yi Chang and Huan Liu.
Recommendation with Social Dimensions
the AAAI Conference on Artificial Intelligence (AAAI), 2016
Publications in 2015
[1] Jiliang Tang and Huan Liu.
Trust in Social Media
Morgan Claypool & Publishers, 2015
[2] Suhang Wang, Jiliang Tang and Huan Liu.
Feature Selection
Encyclopedia of Machine Learning and Data Mining, 2015
[3] Jiliang Tang, Huiji Gao, Atish Das Sarma, Yingzhou Bi and Huan Liu.
Trust Evolution: Modeling and Its Applications
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2015
[4] Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang and Huan Liu.
Facilitating Time-Critical Information Seeking in Social Media
the IEEE International Conference on Data Mining (ICDM), 2015
[5] Yunzhong Liu, Yi Chen, Jiliang Tang and Huan Liu.
Context-Aware Experience Extraction from Online Health Forums
IEEE International Conference on Healthcare Informatics (ICHI), 2015
[6] Suhang Wang, Jiliang Tang and Huan Liu.
Toward Dual Roles of Users in Recommender Systems
ACM International Conference of Information and Knowledge Management (CIKM), 2015
[7] Jundong Li, Xia Hu, Jiliang Tang and Huan Liu.
Unsupervised Streaming Feature Selection in Social Media
ACM International Conference of Information and Knowledge Management (CIKM), 2015
[8] Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu Aggarwal and Thomas Huang.
Heterogeneous Network Embedding via Deep Architectures
ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD), 2015
[9] Suhang Wang, Jiliang Tang, Yilin Wang and Huan Liu.
Exploring Implicit Hierarchical Structures for Recommender Systems
International Joint Conference on Artificial Intelligence (IJCAI), 2015
[10] Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu and Baoxin Li.
Unsupervised Sentiment Analysis for Social Media Images
International Joint Conference on Artificial Intelligence (IJCAI), 2015 [Project Webpage]
[11] Jiliang Tang, Chikashi Nobata, Anlei Dong, Yi Chang and Huan Liu.
Propagation-based Sentiment Analysis for Microblogging Data
SIAM International Conference on Data Mining (SDM), 2015
[12] Suhang Wang, Jiliang Tang and Huan Liu.
Embedded Unsupervised Feature Selection
the AAAI Conference on Artificial Intelligence (AAAI), 2015
[13] Huiji Gao, Jiliang Tang, Xia Hu and Huan Liu.
Content-Aware Point of Interest Recommendation on Location-Based Social Networks
the AAAI Conference on Artificial Intelligence (AAAI), 2015
[14] Suhas Ranganath, Jiliang Tang, Xia Hu, Hari Sundaram and Huan Liu.
Leveraging Social Foci for Information Seeking in Social Media
the AAAI Conference on Artificial Intelligence (AAAI), 2015
[15] Ying Wang, Xin Wang, Jiliang Tang, Wanli Zuo and Guoyong Cai.
Modeling Status Theory in Trust Prediction
the AAAI Conference on Artificial Intelligence (AAAI), 2015
[16] Jiliang Tang, Shiyu Chang, Charu Aggarwal and Huan Liu.
Negative Link Prediction in Social Media
[Slides]
ACM International Conference on Web Search and Data Mining (WSDM), 2015
Publications in 2014
[1] Mohammad Ali Abbasi, Jiliang Tang and Huan Liu.
Trust Aware Recommender Systems
in Machine Learning book on computational trust, Chapman and Hall/CRC Press
[2] Jiliang Tang, Salem Alelyani and Huan Liu.
Feature Selection for Classification: A Review
in Data Classification: Algorithms and Applications. Editor: Charu Aggarwal, CRC Press
[3] Pritam Gundecha , Geoffrey Barbier, Jiliang Tang and Huan Liu.
User Vulnerability and its Reduction on a Social Networking Site
ACM Transactions on Knowledge Discovery from Data (TKDD), 2014
[4] Jiliang Tang and Huan Liu.
An Unsupervised Feature Selection Framework for Social Media Data
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2014
[5] Jiliang Tang and Huan Liu.
Feature Selection for Social Media Data
ACM Transactions on Knowledge Discovery from Data (TKDD), 2014
[6] Huiji Gao, Jiliang Tang and Huan Liu.
Solving the Cold Start Problem in Location Recommendation with Geo-Social Correlations
Data mining and Knowledge Discovery (DMKD), 2014
[7] Huiji Gao, Jiliang Tang and Huan Liu.
Personalized Location Recommendation on Location-based Social Network
Tutorial on The ACM Recommender System conference (Recsys), 2014
[8] Jiliang Tang, Jie Tang and Huan Liu.
Recommendation in Social Media - Recent Advances and New Frontier
Tutorial on 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014
[9] Jiliang Tang and Huan Liu.
Trust in Social Computing
Tutorial on the 23nd International World Wide Web Conference (WWW), 2014
[10] Xia Hu, Jiliang Tang, Huiji Gao and Huan Liu.
Social Spammer Detection with Sentiment Information
IEEE International Conference on Data Mining (ICDM), 2014
[11] Jiliang Tang, Xia Hu, Yi Chang and Huan Liu.
Predictability of Distrust with Interaction Data
ACM International Conference on Information and Knowledge Management (CIKM), 2014
[12] Jiliang Tang, Xia Hu and Huan Liu.
Is Distrust the Negation of Trust? The Value of Distrust in Social Media
ACM Hypertext conference (HT), 2014
[13] Mohammad Ali Abbasi, Reza Zafarani, Jiliang Tang and Huan Liu.
Am I More Similar to My Followers or Followees? Homophily Effect in Directed Online Social Networks
ACM Hypertext conference (HT), 2014
[14] Mohammad Ali Abbasi, Jiliang Tang and Huan Liu.
Scalable Learning of Users' Preferences Using Networked Data
ACM Hypertext conference (HT), 2014
[15] Guoyong Cai, Jiliang Tang, Yiming Wen.
Trust Prediction with Temporal Dynamics
Web-Age Information Management, 2014
[16] Xia Hu, Jiliang Tang and Huan Liu.
Leveraging Knowledge across Media for Spammer Detection in Microblogging
In Proceedings of the 37th Annual ACM SIGIR Conference (SIGIR), 2014.
[17] Xia Hu, Jiliang Tang and Huan Liu.
Online Social Spammer Detection
In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI), 2014
[18] Jiliang Tang, Xia Hu, Huiji Gao and Huan Liu.
Discriminant Analysis for Unsupervised Feature Selection
the 14th SIAM International Conference on Data Mining (SDM), 2014
Publications in 2013
[1] Salem Alelyani, Jiliang Tang and Huan Liu.
Feature Selection for Clustering: A Review
in Data Clustering: Algorithms and Applications, Editor: Charu Aggarwal and Chandan Reddy, CRC Press.
[2] Jiliang Tang , Yi Chang and Huan Liu.
Mining Social Media with Social Theories: A Survey
SIGKDD Explorations, 2013
[3] Jiliang Tang , Xia Hu and Huan Liu.
Social Recommendation: A Review
Social Network Analysis and Mining (SNAM), 2013
[4] Huiji Gao, Jiliang Tang, Xia Hu and Huan Liu.
Modeling Temporal Effects of Human Mobile Behavior on Location-Based Social Networks
ACM International Conference on Information and Knowledge Management (CIKM), 2013
[5] Jiliang Tang , Huiji Gao, Xia Hu and Huan Liu.
Context-Aware Review Helpfulness Rating Prediction
the ACM Conference Series on Recommender Systems (RecSys), 2013
[6] Huiji Gao, Jiliang Tang, Xia Hu and Huan Liu.
Exploring Temporal Effects for Location Recommendation on Location-Based Social Networks
the ACM Conference Series on Recommender Systems (RecSys), 2013
[7] Huiji Gao, Xufei Wang, Jiliang Tang and Huan Liu.
Network Denoising in Social Media
the 2013 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), 2013
[8] Jiliang Tang, Xia Hu, Huiji Gao and Huan Liu.
Exploiting Local and Global Social Context for Recommendation
the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
[9] Xia Hu, Jiliang Tang, Yanchao Zhang and Huan Liu.
Social Spammer Detection in Microblogging
the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
[10] Xia Hu, Jiliang Tang, Huiji Gao and Huan Liu.
Unsupervised Sentiment Analysis with Emotional Signals
the 22nd International World Wide Web Conference (WWW), 2013
[11] Jiliang Tang and Huan Liu.
CoSelect: Feature Selection with Instance Selection for Social Media Data
the 13th SIAM International Conference on Data Mining (SDM), 2013
[12] Jiliang Tang, Xia Hu, Huiji Gao and Huan Liu.
Unsupervised Feature Selection for Multi-view Data in Social Media
the 13th SIAM International Conference on Data Mining (SDM), 2013
[13] Xia Hu, jiliang Tang, Huiji Gao and Huan Liu.
ActNeT: Active Learning for Networked Texts in Microblogging
the 13th SIAM International Conference on Data Mining (SDM), 2013
[14] Jiliang Tang, Huiji Gao, Xia Hu and Huan Liu.
Exploiting Homophily Effect for Trust Prediction
the 6th ACM International Conference on Web Search and Data Mining (WSDM), 2013
[15] Xia Hu, Lei Tang, Jiliang Tang and Huan Liu.
Exploiting Social Relations for Sentiment Analysis in Microblogging
the 6th ACM International Conference on Web Search and Data Mining (WSDM), 2013
Publications in 2012 and Before
[1] Huiji Gao, Jiliang Tang and Huan Liu.
gSCorr: Modeling Geo-Social Correlations for New Check-ins on Location-Based Social Networks
ACM International Conference on Information and Knowledge Management (CIKM), 2012
[2] Huiji Gao, Jiliang Tang and Huan Liu.
Mobile Location Prediction in Spatio-Temporal Context
Nokia Mobile Data Challenge Workshop 2012
The 3rd Place Dedicated Task 2: Next Location Prediction
[3] Jiliang Tang and Huan Liu.
Unsupervised Feature Selection for Linked Social Media Data
[video]
the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012
[4] Jiliang Tang, Huiji Gao, Huan Liu and Atish Das Sarma.
eTrust: Understanding Trust Evolution in an Online World
[video]
the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012
[5] Huiji Gao, Jiliang Tang, Huan Liu.
Exploring Social-Historical Ties on Location-Based Social Networks
the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM), 2012
[6] Jiliang Tang, Huan Liu.
Feature Selection with Linked Data in Social Media
SIAM International Conference on Data Mining (SDM), 2012
[7] Jiliang Tang, Huiji Gao and Huan Liu.
mTrust: Discerning Multi-Faceted Trust in a Connected World
the 5th ACM International Conference on Web Search and Data Mining (WSDM), 2012
[8] Jiliang Tang, Xufei Wang, Huiji Gao, Xia Hu and Huan Liu.
Enriching Short Texts Representation in MicroBlog for Clustering
[Dataset]
Frontiers of Computer Science, 2012
[9] Jiliang Tang, Xufei Wang and Huan Liu.
Integrating Social Media Data for Community Detection
MSM-MUSE, 2011
[10] Xufei Wang, Jiliang Tang, Huan Liu.
Document Clustering via Matrix Representation
the 11th IEEE International Conference on Data Mining (ICDM), 2011