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- affiliation: Michigan State University, East Lansing, MI, USA
- affiliation (Ph.D.): Arizona State University, Tempe, Arizona, USA
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2020 – today
- 2023
[j40]Xin Juan, Fengfeng Zhou, Wentao Wang, Wei Jin, Jiliang Tang, Xin Wang:
INS-GNN: Improving graph imbalance learning with self-supervision. Inf. Sci. 637: 118935 (2023)- [j39]Haochen Liu
, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Yunhao Liu, Anil K. Jain, Jiliang Tang:
Trustworthy AI: A Computational Perspective. ACM Trans. Intell. Syst. Technol. 14(1): 4:1-4:59 (2023) - [j38]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. ACM Trans. Inf. Syst. 41(2): 43:1-43:27 (2023) - [c192]Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang:
Toward Degree Bias in Embedding-Based Knowledge Graph Completion. WWW 2023: 705-715 - [i117]Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li:
Generative Diffusion Models on Graphs: Methods and Applications. CoRR abs/2302.02591 (2023) - [i116]Hongzhi Wen, Wenzhuo Tang, Wei Jin, Jiayuan Ding, Renming Liu, Feng Shi, Yuying Xie, Jiliang Tang:
Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation. CoRR abs/2302.03038 (2023) - [i115]Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang:
Toward Degree Bias in Embedding-Based Knowledge Graph Completion. CoRR abs/2302.05044 (2023) - [i114]Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang:
Single-Cell Multimodal Prediction via Transformers. CoRR abs/2303.00233 (2023) - [i113]Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang:
Sharpness-Aware Data Poisoning Attack. CoRR abs/2305.14851 (2023) - [i112]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. CoRR abs/2305.15822 (2023) - 2022
- [j37]Rui Miao, Yintao Yang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, Ying Wang, Xin Wang:
Negative samples selecting strategy for graph contrastive learning. Inf. Sci. 613: 667-681 (2022) - [j36]K. Selçuk Candan, Huan Liu, Leman Akoglu, Xin Luna Dong, Jiliang Tang, Andrew Tomkins:
ACM WSDM 2022 report. SIGWEB Newsl. 2022(Summer): 1:1-1:6 (2022) - [j35]Wenqi Fan, Yao Ma, Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang, Dawei Yin:
A Graph Neural Network Framework for Social Recommendations. IEEE Trans. Knowl. Data Eng. 34(5): 2033-2047 (2022) - [j34]Wentao Wang, Guowei Xu, Wenbiao Ding, Gale Yan Huang, Guoliang Li, Jiliang Tang, Zitao Liu:
Representation Learning From Limited Educational Data With Crowdsourced Labels. IEEE Trans. Knowl. Data Eng. 34(6): 2886-2898 (2022) - [c191]Xiangyu Zhao, Wenqi Fan, Hui Liu, Jiliang Tang:
Multi-Type Urban Crime Prediction. AAAI 2022: 4388-4396 - [c190]Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu, Jiliang Tang:
Toward Annotator Group Bias in Crowdsourcing. ACL (1) 2022: 1797-1806 - [c189]Pengfei He, Haochen Liu, Xiangyu Zhao, Hui Liu, Jiliang Tang:
PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations. CIKM 2022: 3152-3161 - [c188]Jamell Dacon, Haochen Liu, Jiliang Tang:
Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference. COLING 2022: 1442-1454 - [c187]Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang:
Imbalanced Adversarial Training with Reweighting. ICDM 2022: 1209-1214 - [c186]Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang:
Is Homophily a Necessity for Graph Neural Networks? ICLR 2022 - [c185]Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang:
Automated Self-Supervised Learning for Graphs. ICLR 2022 - [c184]Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah:
Graph Condensation for Graph Neural Networks. ICLR 2022 - [c183]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. KDD 2022: 709-719 - [c182]Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin:
Condensing Graphs via One-Step Gradient Matching. KDD 2022: 720-730 - [c181]Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang:
Graph Neural Networks for Multimodal Single-Cell Data Integration. KDD 2022: 4153-4163 - [c180]Parker Erickson, Victor E. Lee, Feng Shi, Jiliang Tang:
Efficient Machine Learning on Large-Scale Graphs. KDD 2022: 4788-4789 - [c179]Wentao Wang, Han Xu, Yuxuan Wan, Jie Ren, Jiliang Tang:
Towards Adversarial Learning: From Evasion Attacks to Poisoning Attacks. KDD 2022: 4830-4831 - [c178]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2022). KDD 2022: 4906-4907 - [c177]Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Jiliang Tang, Weiqi Luo:
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models. NeurIPS 2022 - [c176]Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin:
A Large Scale Search Dataset for Unbiased Learning to Rank. NeurIPS 2022 - [c175]Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie, Jiliang Tang:
Localized Graph Collaborative Filtering. SDM 2022: 540-548 - [c174]Wentao Wang, Joseph Thekinen, Xiaorui Liu, Zitao Liu, Jiliang Tang:
Learning from Imbalanced Crowdsourced Labeled Data. SDM 2022: 594-602 - [c173]Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li:
Graph Trend Filtering Networks for Recommendation. SIGIR 2022: 112-121 - [c172]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c171]Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Hui Liu, Jiliang Tang, Youlong Cheng:
Rating Distribution Calibration for Selection Bias Mitigation in Recommendations. WWW 2022: 2048-2057 - [e3]K. Selcuk Candan, Huan Liu, Leman Akoglu, Xin Luna Dong, Jiliang Tang:
WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022. ACM 2022, ISBN 978-1-4503-9132-0 [contents] - [i111]Hongzhi Wen, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang:
Graph Neural Networks for Multimodal Single-Cell Data Integration. CoRR abs/2203.01884 (2022) - [i110]Juan-Hui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin:
Graph Enhanced BERT for Query Understanding. CoRR abs/2204.06522 (2022) - [i109]Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR abs/2204.08570 (2022) - [i108]Yaxin Li, Xiaorui Liu, Han Xu, Wentao Wang, Jiliang Tang:
Enhancing Adversarial Training with Feature Separability. CoRR abs/2205.00637 (2022) - [i107]Juan-Hui 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? CoRR abs/2205.10652 (2022) - [i106]Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang:
Defense Against Gradient Leakage Attacks via Learning to Obscure Data. CoRR abs/2206.00769 (2022) - [i105]Haoyu Han, Xiaorui Liu, Torkamani Ali, Feng Shi, Victor Lee, Jiliang Tang:
Alternately Optimized Graph Neural Networks. CoRR abs/2206.03638 (2022) - [i104]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR abs/2206.07743 (2022) - [i103]Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Ying:
Condensing Graphs via One-Step Gradient Matching. CoRR abs/2206.07746 (2022) - [i102]Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Jiliang Tang, Weiqi Luo:
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models. CoRR abs/2206.11460 (2022) - [i101]Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin:
A Large Scale Search Dataset for Unbiased Learning to Rank. CoRR abs/2207.03051 (2022) - [i100]Jamell Dacon, Harry Shomer, Shaylynn Crum-Dacon, Jiliang Tang:
Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals. CoRR abs/2207.10032 (2022) - [i99]Harry Shomer, Wei Jin, Juan-Hui Li, Yao Ma, Jiliang Tang:
Learning Representations for Hyper-Relational Knowledge Graphs. CoRR abs/2208.14322 (2022) - [i98]Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah:
Empowering Graph Representation Learning with Test-Time Graph Transformation. CoRR abs/2210.03561 (2022) - [i97]Yiqi Wang, Chaozhuo Li, Wei Jin, Rui Li, Jianan Zhao, Jiliang Tang, Xing Xie:
Test-Time Training for Graph Neural Networks. CoRR abs/2210.08813 (2022) - [i96]Pengfei He, Han Xu, Jie Ren, Yuxuan Wan, Zitao Liu, Jiliang Tang:
Probabilistic Categorical Adversarial Attack & Adversarial Training. CoRR abs/2210.09364 (2022) - [i95]Han Xu, Xiaorui Liu, Yuxuan Wan, Jiliang Tang:
Towards Fair Classification against Poisoning Attacks. CoRR abs/2210.09503 (2022) - [i94]Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang:
Transferable Unlearnable Examples. CoRR abs/2210.10114 (2022) - [i93]Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin:
Whole Page Unbiased Learning to Rank. CoRR abs/2210.10718 (2022) - [i92]Dylan Molho, Jiayuan Ding, Zhaoheng Li, Hongzhi Wen, Wenzhuo Tang, Yixin Wang, Julian Venegas, Wei Jin, Renming Liu, Runze Su, Patrick Danaher, Robert Yang, Yu Leo Lei, Yuying Xie, Jiliang Tang:
Deep Learning in Single-Cell Analysis. CoRR abs/2210.12385 (2022) - 2021
- [j33]Feng Xia, Teng Guo, Xiaomei Bai, Adrian Shatte, Zitao Liu, Jiliang Tang:
SUMMER: Bias-aware Prediction of Graduate Employment Based on Educational Big Data. Trans. Data Sci. 2(4): 39:1-39:24 (2021) - [j32]Masoud Zarifneshat, Li Xiao, Jiliang Tang, Xinyu Zhang:
Learning-based blockage prediction for robust links in dynamic millimeter wave networks. Wirel. Networks 27(7): 4693-4714 (2021) - [c170]Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Jiliang Tang, Hui Liu:
DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems. AAAI 2021: 750-758 - [c169]Yaxin Li, Wei Jin, Han Xu, Jiliang Tang:
DeepRobust: a Platform for Adversarial Attacks and Defenses. AAAI 2021: 16078-16080 - [c168]Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang:
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. ACL/IJCNLP (Findings) 2021: 74-85 - [c167]Yang Hao, Hang Li, Wenbiao Ding, Zhongqin Wu, Jiliang Tang, Rose Luckin, Zitao Liu:
Multi-task Learning Based Online Dialogic Instruction Detection with Pre-trained Language Models. AIED (2) 2021: 183-189 - [c166]Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao, Qiang Fang, Wenbiao Ding, Zhongqin Wu, Feng Xia, Jiliang Tang, Zitao Liu:
Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models. AIED (2) 2021: 256-261 - [c165]Hamid Karimi, Jiliang Tang, Xochitl Weiss, Jiangtao Huang:
Automatic Identification of Teachers in Social Media using Positive Unlabeled Learning. IEEE BigData 2021: 643-652 - [c164]Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu, Jiliang Tang:
Deep Adversarial Network Alignment. CIKM 2021: 352-361 - [c163]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CIKM 2021: 813-822 - [c162]Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah:
A Unified View on Graph Neural Networks as Graph Signal Denoising. CIKM 2021: 1202-1211 - [c161]Aaron Brookhouse, Tyler Derr, Hamid Karimi, H. Russell Bernard, Jiliang Tang:
Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries. HT 2021: 57-66 - [c160]Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li:
Attacking Black-box Recommendations via Copying Cross-domain User Profiles. ICDE 2021: 1583-1594 - [c159]Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, Xiwang Yang:
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations. ICDM 2021: 896-905 - [c158]Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan:
Linear Convergent Decentralized Optimization with Compression. ICLR 2021 - [c157]Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang:
Elastic Graph Neural Networks. ICML 2021: 6837-6849 - [c156]Han Xu, Xiaorui Liu, Yaxin Li, Anil K. Jain, Jiliang Tang:
To be Robust or to be Fair: Towards Fairness in Adversarial Training. ICML 2021: 11492-11501 - [c155]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c154]Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, Jiliang Tang:
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection. KDD 2021: 3726-3734 - [c153]Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang:
AutoLoss: Automated Loss Function Search in Recommendations. KDD 2021: 3959-3967 - [c152]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c151]Han Xu, Yaxin Li, Xiaorui Liu, Wentao Wang, Jiliang Tang:
Adversarial Robustness in Deep Learning: From Practices to Theories. KDD 2021: 4086-4087 - [c150]Lingfei Wu, Jiliang Tang, Yinglong Xia, Jian Pei, Xiaojie Guo:
The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21). KDD 2021: 4167-4168 - [c149]Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang:
Graph Neural Networks with Adaptive Residual. NeurIPS 2021: 9720-9733 - [c148]Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang:
Yet Meta Learning Can Adapt Fast, it Can Also Break Easily. SDM 2021: 540-548 - [c147]Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang:
Node Similarity Preserving Graph Convolutional Networks. WSDM 2021: 148-156 - [c146]Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long:
AutoDim: Field-aware Embedding Dimension Searchin Recommender Systems. WWW 2021: 3015-3022 - [c145]Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang:
UserSim: User Simulation via Supervised GenerativeAdversarial Network. WWW 2021: 3582-3589 - [i91]Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang:
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. CoRR abs/2105.02778 (2021) - [i90]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CoRR abs/2105.04493 (2021) - [i89]Han Xu, Xiaorui Liu, Wentao Wang, Wenbiao Ding, Zhongqin Wu, Zitao Liu, Anil K. Jain, Jiliang Tang:
Towards the Memorization Effect of Neural Networks in Adversarial Training. CoRR abs/2106.04794 (2021) - [i88]Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang:
Automated Self-Supervised Learning for Graphs. CoRR abs/2106.05470 (2021) - [i87]Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang:
Is Homophily a Necessity for Graph Neural Networks? CoRR abs/2106.06134 (2021) - [i86]Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang:
AutoLoss: Automated Loss Function Search in Recommendations. CoRR abs/2106.06713 (2021) - [i85]Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Anil K. Jain, Jiliang Tang:
Trustworthy AI: A Computational Perspective. CoRR abs/2107.06641 (2021) - [i84]Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang:
Elastic Graph Neural Networks. CoRR abs/2107.06996 (2021) - [i83]Yang Hao, Hang Li, Wenbiao Ding, Zhongqin Wu, Jiliang Tang, Rose Luckin, Zitao Liu:
Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models. CoRR abs/2107.07119 (2021) - [i82]Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao, Qiang Fang, Wenbiao Ding, Zhongqin Wu, Feng Xia, Jiliang Tang, Zitao Liu:
Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models. CoRR abs/2107.07122 (2021) - [i81]Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang:
Imbalanced Adversarial Training with Reweighting. CoRR abs/2107.13639 (2021) - [i80]Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. CoRR abs/2108.03388 (2021) - [i79]Yao Li, Xiaorui Liu, Jiliang Tang, Ming Yan, Kun Yuan:
Decentralized Composite Optimization with Compression. CoRR abs/2108.04448 (2021) - [i78]Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li:
Graph Trend Networks for Recommendations. CoRR abs/2108.05552 (2021) - [i77]Jamell Dacon, Jiliang Tang:
What Truly Matters? Using Linguistic Cues for Analyzing the #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020. CoRR abs/2109.12192 (2021) - [i76]Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah:
Graph Condensation for Graph Neural Networks. CoRR abs/2110.07580 (2021) - [i75]Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu, Jiliang Tang:
Toward Annotator Group Bias in Crowdsourcing. CoRR abs/2110.08038 (2021) - [i74]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. CoRR abs/2112.07191 (2021) - 2020
- [j31]Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain:
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. Int. J. Autom. Comput. 17(2): 151-178 (2020) - [j30]Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang:
Adversarial Attacks and Defenses on Graphs. SIGKDD Explor. 22(2): 19-34 (2020) - [j29]Tyler Derr, Zhiwei Wang, Jamell Dacon, Jiliang Tang:
Link and interaction polarity predictions in signed networks. Soc. Netw. Anal. Min. 10(1): 18 (2020) - [j28]Ghazaleh Beigi, Jiliang Tang, Huan Liu:
Social Science-guided Feature Engineering: A Novel Approach to Signed Link Analysis. ACM Trans. Intell. Syst. Technol. 11(1): 11:1-11:27 (2020) - [c144]Teng Guo, Feng Xia, Shihao Zhen, Xiaomei Bai, Dongyu Zhang, Zitao Liu, Jiliang Tang:
Graduate Employment Prediction with Bias. AAAI 2020: 670-677 - [c143]Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu:
Learning Multi-Level Dependencies for Robust Word Recognition. AAAI 2020: 9250-9257 - [c142]Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank, Jiliang Tang:
Towards Improving Sample Representativeness of Teachers on Online Social Media: A Case Study on Pinterest. AIED (2) 2020: 130-134 - [c141]Hang Li, Zhiwei Wang, Jiliang Tang, Wenbiao Ding, Zitao Liu:
Siamese Neural Networks for Class Activity Detection. AIED (2) 2020: 162-167 - [c140]Gale Yan Huang, Jiahao Chen, Haochen Liu, Weiping Fu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Guoliang Li, Zitao Liu:
Neural Multi-task Learning for Teacher Question Detection in Online Classrooms. AIED (1) 2020: 269-281 - [c139]Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan:
A Double Residual Compression Algorithm for Efficient Distributed Learning. AISTATS 2020: 133-143 - [c138]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks. CIKM 2020: 1435-1444 - [c137]Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang:
Whole-Chain Recommendations. CIKM 2020: 1883-1891 - [c136]Haochen Liu, Zitao Liu, Zhongqin Wu, Jiliang Tang:
Personalized Multimodal Feedback Generation in Education. COLING 2020: 1826-1840 - [c135]Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu, Jiliang Tang:
Does Gender Matter? Towards Fairness in Dialogue Systems. COLING 2020: 4403-4416 - [c134]Hamid Karimi, Tyler Derr, Jiangtao Huang, Jiliang Tang:
Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network. EDM 2020 - [c133]