Graph-Based Iterative Hybrid Feature Selection. - ErHeng Zhong; Sihong Xie; Wei Fan 001; Jiangtao Ren; Jing Peng 001; Kun Zhang 012 (ICDM, 2008)

Latent space domain transfer between high dimensional overlapping distributions. - Sihong Xie; Wei Fan 001; Jing Peng 001; Olivier Verscheure; Jiangtao Ren (WWW, 2009)

Efficient and Numerically Stable Sparse Learning. - Sihong Xie; Wei Fan 001; Olivier Verscheure; Jiangtao Ren (ECML/PKDD (3), 2010)

Review Graph Based Online Store Review Spammer Detection. - Guan Wang; Sihong Xie; Bing Liu 001; Philip S. Yu (ICDM, 2011)

Relevance search in heterogeneous networks. - Chuan Shi 001; Xiangnan Kong; Philip S. Yu; Sihong Xie; Bin Wu 001 (EDBT, 2012)

Review spam detection via temporal pattern discovery. - Sihong Xie; Guan Wang; Shuyang Lin; Philip S. Yu (KDD, 2012)

An Iterative and Re-weighting Framework for Rejection and Uncertainty Resolution in Crowdsourcing. - Sihong Xie; Wei Fan 001; Philip S. Yu (SDM, 2012)

Review spam detection via time series pattern discovery. - Sihong Xie; Guan Wang; Shuyang Lin; Philip S. Yu (WWW (Companion Volume), 2012)

Identify Online Store Review Spammers via Social Review Graph. - Guan Wang; Sihong Xie; Bing Liu 001; Philip S. Yu (ACM Trans. Intell. Syst. Technol., 2012)

An effective latent networks fusion based model for event recommendation in offline ephemeral social networks. - Guoqiong Liao; Yuchen Zhao; Sihong Xie; Philip S. Yu (CIKM, 2013)

Multilabel Consensus Classification. - Sihong Xie; Xiangnan Kong; Jing Gao 004; Wei Fan 001; Philip S. Yu (ICDM, 2013)

Latent Networks Fusion based Model for Event Recommendation in Offline Ephemeral Social Networks. - Guoqiong Liao; Yuchen Zhao; Sihong Xie; Philip S. Yu (CoRR, 2013)

Class-distribution regularized consensus maximization for alleviating overfitting in model combination. - Sihong Xie; Jing Gao 004; Wei Fan 001; Deepak S. Turaga; Philip S. Yu (KDD, 2014)

Trajectory Event Cleaning for Mobile RFID Objects. - Guoqiong Liao; Philip S. Yu; Qianhui Zhong; Sihong Xie; Zhen Shen; Changxuan Wan; Dexi Liu (MDM (1), 2014)

Future Influence Ranking of Scientific Literature. - Senzhang Wang; Sihong Xie; Xiaoming Zhang 001; Zhoujun Li 001; Philip S. Yu; Xinyu Shu (SDM, 2014)

Inferring the impacts of social media on crowdfunding. - Chun-Ta Lu; Sihong Xie; Xiangnan Kong; Philip S. Yu (WSDM, 2014)

Robust crowd bias correction via dual knowledge transfer from multiple overlapping sources. - Sihong Xie; Qingbo Hu; Jingyuan Zhang; Jing Gao 004; Wei Fan 001; Philip S. Yu (IEEE BigData, 2015)

Learning Entity Types from Query Logs via Graph-Based Modeling. - Jingyuan Zhang; Luo Jie; Altaf Rahman; Sihong Xie; Yi Chang 001; Philip S. Yu (CIKM, 2015)

An effective and economic bi-level approach to ranking and rating spam detection. - Sihong Xie; Qingbo Hu; Jingyuan Zhang; Philip S. Yu (DSAA, 2015)

A context-aware approach to detection of short irrelevant texts. - Sihong Xie; Jing Wang 102; Mohammad Shafkat Amin; Baoshi Yan; Anmol Bhasin; Clement T. Yu; Philip S. Yu (DSAA, 2015)

CENI: A Hybrid Framework for Efficiently Inferring Information Networks. - Qingbo Hu; Sihong Xie; Shuyang Lin; Senzhang Wang; Philip S. Yu (ICWSM, 2015)

OnlineCM: Real-time Consensus Classification with Missing Values. - Bowen Dong; Sihong Xie; Jing Gao 004; Wei Fan 001; Philip S. Yu (SDM, 2015)

Frameworks to Encode User Preferences for Inferring Topic-sensitive Information Networks. - Qingbo Hu; Sihong Xie; Shuyang Lin; Wei Fan 001; Philip S. Yu (SDM, 2015)

Efficient Partial Order Preserving Unsupervised Feature Selection on Networks. - Xiaokai Wei; Sihong Xie; Philip S. Yu (SDM, 2015)

Constructing plausible innocuous pseudo queries to protect user query intention. - Zongda Wu; Jie Shi; Chenglang Lu; Enhong Chen; Guandong Xu; Guiling Li; Sihong Xie; Philip S. Yu (Inf. Sci., 2015)

CER: Complementary entity recognition via knowledge expansion on large unlabeled product reviews. - Hu Xu 001; Sihong Xie; Lei Shu 004; Philip S. Yu (IEEE BigData, 2016)

Interpretable and effective opinion spam detection via temporal patterns mining across websites. - Yuan Yuan 016; Sihong Xie; Chun-Ta Lu; Jie Tang 001; Philip S. Yu (IEEE BigData, 2016)

HEER: Heterogeneous graph embedding for emerging relation detection from news. - Jingyuan Zhang; Chun-Ta Lu; Mianwei Zhou; Sihong Xie; Yi Chang 001; Philip S. Yu (IEEE BigData, 2016)

Active Zero-Shot Learning. - Sihong Xie; Shaoxiong Wang; Philip S. Yu (CIKM, 2016)

Multi-source Hierarchical Prediction Consolidation. - Chenwei Zhang; Sihong Xie; Yaliang Li; Jing Gao 004; Wei Fan 001; Philip S. Yu (CIKM, 2016)

Item Recommendation for Emerging Online Businesses. - Chun-Ta Lu; Sihong Xie; Weixiang Shao; Lifang He 001; Philip S. Yu (IJCAI, 2016)

Effective Crowd Expertise Modeling via Cross Domain Sparsity and Uncertainty Reduction. - Sihong Xie; Qingbo Hu; Weixiang Shao; Jingyuan Zhang; Jing Gao 004; Wei Fan 001; Philip S. Yu (SDM, 2016)

Identifying Connectivity Patterns for Brain Diseases via Multi-side-view Guided Deep Architectures. - Jingyuan Zhang; Bokai Cao; Sihong Xie; Chun-Ta Lu; Philip S. Yu; Ann B. Ragin (SDM, 2016)

Two-Phase Mining for Frequent Closed Episodes. - Guoqiong Liao; Xiaoting Yang; Sihong Xie; Philip S. Yu; Changxuan Wan (WAIM (1), 2016)

HeteroSales: Utilizing Heterogeneous Social Networks to Identify the Next Enterprise Customer. - Qingbo Hu; Sihong Xie; Jiawei Zhang 001; Qiang Zhu 002; Songtao Guo; Philip S. Yu (WWW, 2016)

Clustering Embedded Approaches for Efficient Information Network Inference. - Qingbo Hu; Sihong Xie; Shuyang Lin; Senzhang Wang; Philip S. Yu (Data Sci. Eng., 2016)

Coranking the Future Influence of Multiobjects in Bibliographic Network Through Mutual Reinforcement. - Senzhang Wang; Sihong Xie; Xiaoming Zhang 001; Zhoujun Li 001; Philip S. Yu; Yueying He (ACM Trans. Intell. Syst. Technol., 2016)

Efficient Revenue Maximization for Viral Marketing in Social Networks. - Yuan Su; Xi Zhang 008; Sihong Xie; Philip S. Yu; Binxing Fang (ADMA, 2017)

Product function need recognition via semi-supervised attention network. - Hu Xu 001; Sihong Xie; Lei Shu 004; Philip S. Yu (IEEE BigData, 2017)

SEVEN: Deep Semi-supervised Verification Networks. - Vahid Noroozi; Lei Zheng 001; Sara Bahaadini; Sihong Xie; Philip S. Yu (IJCAI, 2017)

Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-Links. - Xiaokai Wei; Sihong Xie; Bokai Cao; Philip S. Yu (ECML/PKDD (1), 2017)

Active zero-shot learning: a novel approach to extreme multi-labeled classification. - Sihong Xie; Philip S. Yu (Int. J. Data Sci. Anal., 2017)

基于无监督学习的移动心电信号异常诊断研究 (Study on Abnormal Diagnosis of Moving ECG Signals Based on Unsupervised Learning). - Feng Li; Sihong Xie (计算机科学, 2017)

Probabilistic cleaning over trajectory events of mobile RFID objects. - Guoqiong Liao; Philip S. Yu; Qianhui Zhong; Sihong Xie; Changxuan Wan; Dexi Liu (ACM SIGSPATIAL Special, 2017)

Dual Attention Network for Product Compatibility and Function Satisfiability Analysis. - Hu Xu 001; Sihong Xie; Lei Shu 004; Philip S. Yu (AAAI, 2018)

Securing Behavior-based Opinion Spam Detection. - Shuaijun Ge; Guixiang Ma; Sihong Xie; Philip S. Yu (IEEE BigData, 2018)

Semi-supervised Deep Representation Learning for Multi-View Problems. - Vahid Noroozi; Sara Bahaadini; Lei Zheng 001; Sihong Xie; Weixiang Shao; Philip S. Yu (IEEE BigData, 2018)

PER: A Probabilistic Attentional Model for Personalized Text Recommendations. - Lei Zheng 001; Yixue Wang; Lifang He 001; Sihong Xie; Fengjiao Wang; Philip S. Yu (IEEE BigData, 2018)

Next Generation Trustworthy Fraud Detection. - Sihong Xie; Philip S. Yu (CIC, 2018)

MARS: Memory Attention-Aware Recommender System. - Lei Zheng 001; Chun-Ta Lu; Lifang He 001; Sihong Xie; Vahid Noroozi; He Huang 008; Philip S. Yu (CoRR, 2018)

Transductive Learning Via Improved Geodesic Sampling. - Youshan Zhang; Sihong Xie; Brian D. Davison 001 (BMVC, 2019)

MARS: Memory Attention-Aware Recommender System. - Lei Zheng 001; Chun-Ta Lu; Lifang He 001; Sihong Xie; He Huang 008; Chaozhuo Li; Vahid Noroozi; Bowen Dong; Philip S. Yu (DSAA, 2019)

Virtual Adversarial Training for Semi-supervised Verification Tasks. - Vahid Noroozi; Sara Bahaadini; Lei Zheng 001; Sihong Xie; Philip S. Yu (EUSIPCO, 2019)

Scalable Explanation of Inferences on Large Graphs. - Chao Chen; Yifei Liu; Xi Zhang 008; Sihong Xie (ICDM, 2019)

IAD: Interaction-Aware Diffusion Framework in Social Networks. - Xi Zhang 008; Yuan Su; Siyu Qu; Sihong Xie; Binxing Fang; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2019)

Shapley Values and Meta-Explanations for Probabilistic Graphical Model Inference. - Yifei Liu; Chao Chen; Yazheng Liu; Xi Zhang 008; Sihong Xie (CIKM, 2020)

Active Search using Meta-Bandits. - Shengli Zhu; Jakob Coles; Sihong Xie (CIKM, 2020)

Robust Spammer Detection by Nash Reinforcement Learning. - Yingtong Dou; Guixiang Ma; Philip S. Yu; Sihong Xie (KDD, 2020)

Rigorous Explanation of Inference on Probabilistic Graphical Models. - Yifei Liu; Chao Chen; Xi Zhang 008; Sihong Xie (CoRR, 2020)

Certification and Trade-off of Multiple Fairness Criteria in Graph-based Spam Detection. - Kai Burkholder; Kenny Kwock; Yuesheng Xu; Jiaxin Liu; Chao Chen; Sihong Xie (CIKM, 2021)

Self-learn to Explain Siamese Networks Robustly. - Chao Chen; Yifan Shen; Guixiang Ma; Xiangnan Kong; Srinivas Rangarajan; Xi Zhang 008; Sihong Xie (ICDM, 2021)

Multi-objective Explanations of GNN Predictions. - Yifei Liu; Chao Chen; Yazheng Liu; Xi Zhang 008; Sihong Xie (ICDM, 2021)

Truth Discovery in Sequence Labels from Crowds. - Nasim Sabetpour; Adithya Kulkarni; Sihong Xie; Qi Li 012 (ICDM, 2021)

The Third International TrueFact Workshop: Making a Credible Web for Tomorrow. - Subhabrata Mukherjee; Qi Li 012; Sihong Xie; Philip S. Yu; Jing Gao 004 (KDD, 2021)

Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks. - Hang Yin; John Boaz Lee; Xiangnan Kong; Thomas Hartvigsen; Sihong Xie (KDD, 2021)

Formation Mechanisms and Clustering Differences in Risky Riding Behaviors of Electric Bike Riders. - Tao Wang 068; Yuzhi Chen; Jin Yu; Sihong Xie (IEEE Access, 2021)

Explaining GNN over Evolving Graphs using Information Flow. - Yazheng Liu; Xi Zhang 008; Sihong Xie (CoRR, 2021)

A Predictor-Corrector Method for Multi-objective Optimization in Fair Machine Learning. - Sean Wang 006; Arielle Carr; Sihong Xie (BDCAT, 2022)

Efficient Multiple Objective Optimization for Fair Misinformation Detection. - Eric Enouen; Katja Mathesius; Sean Wang 006; Arielle Carr; Sihong Xie (IEEE Big Data, 2022)

Trade less Accuracy for Fairness and Trade-off Explanation for GNN. - Yazheng Liu; Xi Zhang 008; Sihong Xie (IEEE Big Data, 2022)

Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact). - Pamela Bhattacharya; Jing Gao 004; Meng Jiang 001; Mehran Kafai; Srijan Kumar; Qi Li 012; Neil Shah; Sihong Xie; Philip S. Yu; Ming Zeng 001 (KDD, 2022)

Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection. - Yuefei Lyu; Xiaoyu Yang; Jiaxin Liu; Sihong Xie; Xi Zhang 008 (CoRR, 2022)

Subgroup Fairness in Graph-based Spam Detection. - Jiaxin Liu; Yuefei Lyu; Xi Zhang 008; Sihong Xie (CoRR, 2022)

Efficient first-order predictor-corrector multiple objective optimization for fair misinformation detection. - Eric Enouen; Katja Mathesius; Sean Wang 006; Arielle Carr; Sihong Xie (CoRR, 2022)

Robust Ranking Explanations. - Chao Chen; Chenghua Guo; Guixiang Ma; Xi Zhang 008; Sihong Xie (CoRR, 2022)

A Differential Geometric View and Explainability of GNN on Evolving Graphs. - Yazheng Liu; Xi Zhang 008; Sihong Xie (ICLR, 2023)

Implementing Recycling Methods for Linear Systems in Python with an Application to Multiple Objective Optimization. - Ainara Garcia; Sihong Xie; Arielle Carr (ICMLA, 2023)

Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection. - Yuefei Lyu; Xiaoyu Yang; Jiaxin Liu; Sihong Xie; Philip S. Yu; Xi Zhang 008 (IJCNN, 2023)

Optimal Budget Allocation for Crowdsourcing Labels for Graphs. - Adithya Kulkarni; Mohna Chakraborty; Sihong Xie; Qi Li 012 (UAI, 2023)

Robust Ranking Explanations. - Chao Chen; Chenghua Guo; Guixiang Ma; Ming Zeng; Xi Zhang 008; Sihong Xie (CoRR, 2023)

DetectGPT-SC: Improving Detection of Text Generated by Large Language Models through Self-Consistency with Masked Predictions. - Rongsheng Wang; Qi Li; Sihong Xie (CoRR, 2023)

Inconsistent Matters: A Knowledge-Guided Dual-Consistency Network for Multi-Modal Rumor Detection. - Mengzhu Sun; Xi Zhang 008; Jianqiang Ma; Sihong Xie; Yazheng Liu; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2023)

Periodic Prompt on Dynamic Heterogeneous Graph for Next Basket Recommendation. - Ru-Bin Li; Man-Sheng Chen; Xin-Yu Ding; Changdong Wang 001; Sihong Xie; Shuangyin Liu; Min Chen 003; Mohsen Guizani (ICDM, 2024)

Training for Stable Explanation for Free. - Chao Chen; Chenghua Guo; Rufeng Chen; Guixiang Ma; Ming Zeng; Xiangwen Liao; Xi Zhang 008; Sihong Xie (NeurIPS, 2024)

Linear Uncertainty Quantification of Graphical Model Inference. - Chenghua Guo; Han Yu; Jiaxin Liu; Chao Chen; Qi Li; Sihong Xie; Xi Zhang (NeurIPS, 2024)

Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning. - Yuefei Lyu; Chaozhuo Li; Sihong Xie; Xi Zhang 008 (NeurIPS, 2024)

Robust Conformal Prediction under Distribution Shift via Physics-Informed Structural Causal Model. - Rui Xu; Yue Sun; Chao Chen; Parv Venkitasubramaniam; Sihong Xie (CoRR, 2024)

Incorporating Domain Differential Equations into Graph Convolutional Networks to Lower Generalization Discrepancy. - Yue Sun; Chao Chen; Yuesheng Xu; Sihong Xie; Rick S. Blum; Parv Venkitasubramaniam (CoRR, 2024)

Uncertainty Quantification on Graph Learning: A Survey. - Chao Chen; Chenghua Guo; Rui Xu; Xiangwen Liao; Xi Zhang 008; Sihong Xie; Hui Xiong 001; Philip S. Yu (CoRR, 2024)

Out-of-distribution Detection in Medical Image Analysis: A survey. - Zesheng Hong; Yubiao Yue; Yubin Chen; Huanjie Lin; Yuanmei Luo; Mini Han Wang; Weidong Wang; Jialong Xu; Xiaoqi Yang 008; Zhenzhang Li; Sihong Xie (CoRR, 2024)

Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs. - Xiaqiang Tang; Jian Li; Nan Du; Sihong Xie (AAAI, 2025)

CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language Models. - Xiaqiang Tang; Jian Li; Keyu Hu; Nan Du; Xiaolong Li; Xi Zhang; Weigao Sun; Sihong Xie (ACL (1), 2025)

MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexity. - Xiaqiang Tang; Qiang Gao; Jian Li; Nan Du; Qi Li; Sihong Xie (COLING, 2025)

Explanations of GNN on Evolving Graphs via Axiomatic Layer edges. - Yazheng Liu; Sihong Xie (ICLR, 2025)

Wasserstein-Regularized Conformal Prediction under General Distribution Shift. - Rui Xu; Chao Chen; Yue Sun; Parvathinathan Venkitasubramaniam; Sihong Xie (ICLR, 2025)

Budget Allocation Exploiting Label Correlation between Instances. - Adithya Kulkarni; Mohna Chakraborty; Sihong Xie; Qi Li 012 (UAI, 2025)