Ruocheng Guo

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 120

Top Venues

Publications

Qiang Huang, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang
Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data. ACM Trans. Knowl. Discov. Data 18 (3) (2024)
Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
Tensorized Hypergraph Neural Networks. SDM (2024)
Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
Fair Classifiers that Abstain without Harm. ICLR (2024)
Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction. CoRR (2024)
Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu
Large Language Models for Data Annotation: A Survey. CoRR (2024)
Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao
Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation. CoRR (2024)
Sheng Zhang, Maolin Wang, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao, Zijian Zhang, Hongzhi Yin
EASRec: Elastic Architecture Search for Efficient Long-term Sequential Recommender Systems. CoRR (2024)
Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao
Large Multimodal Model Compression via Iterative Efficient Pruning and Distillation. WWW (Companion Volume) (2024)
Zonghao Chen, Ruocheng Guo, Jean-François Ton, Yang Liu
Conformal Counterfactual Inference under Hidden Confounding. CoRR (2024)
Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu
Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. CoRR (2024)
Maolin Wang, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Zitao Liu, Langming Liu
Cumulative Distribution Function based General Temporal Point Processes. CoRR (2024)
Jingtong Gao, Xiangyu Zhao, Muyang Li, Minghao Zhao, Runze Wu, Ruocheng Guo, Yiding Liu, Dawei Yin
SMLP4Rec: An Efficient All-MLP Architecture for Sequential Recommendations. ACM Trans. Inf. Syst. 42 (3) (2024)
Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu
Conformal Counterfactual Inference under Hidden Confounding. KDD (2024)
Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. CoRR (2023)
Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li
Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. CoRR (2023)
Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu
Equal Opportunity of Coverage in Fair Regression. CoRR (2023)
Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, Ruocheng Guo
Embedding in Recommender Systems: A Survey. CoRR (2023)
Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo
AutoMLP: Automated MLP for Sequential Recommendations. WWW (2023)
Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
Virtual Node Tuning for Few-shot Node Classification. KDD (2023)
Ruocheng Guo, Jean-François Ton, Yang Liu
Fair Learning to Rank with Distribution-free Risk Control. CoRR (2023)
Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
Learning for Counterfactual Fairness from Observational Data. CoRR (2023)
Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li
Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. EMNLP (Findings) (2023)
Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. CoRR (2023)
Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
Virtual Node Tuning for Few-shot Node Classification. CoRR (2023)
Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. CoRR (2023)
Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
Fair Classifiers that Abstain without Harm. CoRR (2023)
Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao
Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup. CoRR (2023)
Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
Learning for Counterfactual Fairness from Observational Data. KDD (2023)
Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, Kasim Selçuk Candan
Causal Disentanglement for Implicit Recommendations with Network Information. ACM Trans. Knowl. Discov. Data 17 (7) (2023)
Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo
AutoMLP: Automated MLP for Sequential Recommendations. CoRR (2023)
Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
Debiasing Recommendation by Learning Identifiable Latent Confounders. KDD (2023)
Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. ICDM (2023)
Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu
Equal Opportunity of Coverage in Fair Regression. NeurIPS (2023)
Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li
Deep Concept Removal. CoRR (2023)
Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
Debiasing Recommendation by Learning Identifiable Latent Confounders. CoRR (2023)
Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. KDD (2023)
Yichuan Li, Kyumin Lee, Nima Kordzadeh, Ruocheng Guo
What Boosts Fake News Dissemination on Social Media? A Causal Inference View. PAKDD (4) (2023)
Maolin Wang, Yaoming Zhen, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
Tensorized Hypergraph Neural Networks. CoRR (2023)
Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. Big Data (2022)
Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, K. Selçuk Candan
Causal Disentanglement with Network Information for Debiased Recommendations. CoRR (2022)
Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. IJCAI (2022)
Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
Learning Fair Node Representations with Graph Counterfactual Fairness. WSDM (2022)
Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
CLEAR: Generative Counterfactual Explanations on Graphs. NeurIPS (2022)
Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
Learning Fair Node Representations with Graph Counterfactual Fairness. CoRR (2022)
Jiayu Shang, Xubo Tang, Ruocheng Guo, Yanni Sun
Accurate identification of bacteriophages from metagenomic data using Transformer. Briefings Bioinform. 23 (4) (2022)
Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. ICWSM (2022)
Lu Cheng, Ruocheng Guo, Huan Liu
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. WSDM (2022)
Lu Cheng, Ruocheng Guo, Huan Liu
Causal Mediation Analysis with Hidden Confounders. WSDM (2022)
Anique Tahir, Lu Cheng, Ruocheng Guo, Huan Liu
Distributional Shift Adaptation using Domain-Specific Features. CoRR (2022)
Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu
Evaluation Methods and Measures for Causal Learning Algorithms. CoRR (2022)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
Graph Few-shot Class-incremental Learning. WSDM (2022)
Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu
Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective. ICDM (2022)
Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selçuk Candan, Huan Liu
Causal Disentanglement with Network Information for Debiased Recommendations. SISAP (2022)
Anique Tahir, Lu Cheng, Ruocheng Guo, Huan Liu
Distributional Shift Adaptation using Domain-Specific Features. Big Data (2022)
Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. CoRR (2022)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
Supervised Graph Contrastive Learning for Few-Shot Node Classification. ECML/PKDD (2) (2022)
Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
CLEAR: Generative Counterfactual Explanations on Graphs. CoRR (2022)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
A Simple Yet Effective Pretraining Strategy for Graph Few-shot Learning. CoRR (2022)
Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu
Evaluation Methods and Measures for Causal Learning Algorithms. IEEE Trans. Artif. Intell. 3 (6) (2022)
Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu
Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective. CoRR (2022)
Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. CoRR (2022)
Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
Causal Understanding of Fake News Dissemination on Social Media. KDD (2021)
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
Graph Few-shot Class-incremental Learning. CoRR (2021)
Lu Cheng, Ruocheng Guo, Huan Liu
Long-Term Effect Estimation with Surrogate Representation. WSDM (2021)
Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu
Adversarial Attacks and Defenses: An Interpretation Perspective. SIGKDD Explor. 23 (1) (2021)
Paras Sheth, Ujun Jeong, Ruocheng Guo, Huan Liu, K. Selçuk Candan
CauseBox: A Causal Inference Toolbox for BenchmarkingTreatment Effect Estimators with Machine Learning Methods. CIKM (2021)
Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu
Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks. Trans. Data Sci. 2 (2) (2021)
Lu Cheng, Ruocheng Guo, Huan Liu
Causal Mediation Analysis with Hidden Confounders. CoRR (2021)
Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
Multi-Cause Effect Estimation with Disentangled Confounder Representation. IJCAI (2021)
Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li
Deconfounding with Networked Observational Data in a Dynamic Environment. WSDM (2021)
Lu Cheng, Ruocheng Guo, Huan Liu
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. CoRR (2021)
Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. CoRR (2021)
Ruocheng Guo, Pengchuan Zhang, Hao Liu, Emre Kiciman
Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix. CoRR (2021)
Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu
Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. CoRR (2020)
Ruocheng Guo, Xiaoting Zhao, Adam Henderson, Liangjie Hong, Huan Liu
Debiasing Grid-based Product Search in E-commerce. KDD (2020)
Ruocheng Guo, Jundong Li, Huan Liu
Learning Individual Causal Effects from Networked Observational Data. WSDM (2020)
Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu
IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data. IJCAI (2020)
Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu
A Survey of Learning Causality with Data: Problems and Methods. ACM Comput. Surv. 53 (4) (2020)
Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu
Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. SIGKDD Explor. 22 (1) (2020)
Ericsson Marin, Ruocheng Guo, Paulo Shakarian
Measuring Time-Constrained Influence to Predict Adoption in Online Social Networks. ACM Trans. Soc. Comput. 3 (3) (2020)
Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
Towards Causal Understanding of Fake News Dissemination. CoRR (2020)
Ruocheng Guo, Jundong Li, Huan Liu
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. SDM (2020)
Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou, Huan Liu
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning. WSDM (2020)
Lu Cheng, Ruocheng Guo, K. Selçuk Candan, Huan Liu
Representation Learning for Imbalanced Cross-Domain Classification. SDM (2020)
Lu Cheng, Ruocheng Guo, Huan Liu
Long-Term Effect Estimation with Surrogate Representation. CoRR (2020)
Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou, Huan Liu
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning. CoRR (2019)
Ruocheng Guo, Jundong Li, Huan Liu
Learning Individual Treatment Effects from Networked Observational Data. CoRR (2019)
Lu Cheng, Ruocheng Guo, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu
A Practical Data Repository for Causal Learning with Big Data. Bench (2019)
Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu
Adaptive Unsupervised Feature Selection on Attributed Networks. KDD (2019)
Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, Huan Liu
Multi-level network embedding with boosted low-rank matrix approximation. ASONAM (2019)
Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu
Privacy Preserving Text Representation Learning. HT (2019)
Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu
I Am Not What I Write: Privacy Preserving Text Representation Learning. CoRR (2019)
Ruocheng Guo, Jundong Li, Huan Liu
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. CoRR (2019)
Ghazaleh Beigi, Ruocheng Guo, Alexander Nou, Yanchao Zhang, Huan Liu
Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles. WSDM (2019)
Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
Using network motifs to characterize temporal network evolution leading to diffusion inhibition. Soc. Netw. Anal. Min. 9 (1) (2019)
Yichuan Li, Ruocheng Guo, Weiying Wang, Huan Liu
Causal Learning in Question Quality Improvement. Bench (2019)
Lu Cheng, Ruocheng Guo, Huan Liu
Robust Cyberbullying Detection with Causal Interpretation. WWW (Companion Volume) (2019)
Elham Shaabani, Ruocheng Guo, Paulo Shakarian
Detecting Pathogenic Social Media Accounts without Content or Network Structure. CoRR (2019)
Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
Using network motifs to characterize temporal network evolution leading to diffusion inhibition. CoRR (2019)
Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu
Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network. SDM (2019)

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Publication Activity (10 Years)

Top Topics

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Ruocheng Guo