Ruocheng Guo - RankMe

150 papers A* 25A 20B 9Journal 83Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Function Calling in Large Language Models: Industrial Practices, Challenges, and Future Directions. ACM Comput. Surv. Maolin Wang, Yingyi Zhang, Bowen Yu, Bingguang Hao, Cunyin Peng, Yicheng Chen, Wei Zhou, Jinjie Gu, Chenyi Zhuang, Ruocheng Guo, Wanyu Wang, Xiangyu Zhao
2026	J	`jnl`	Learning to Rewrite Tool Descriptions for Reliable LLM-Agent Tool Use. CoRR Ruocheng Guo, Kaiwen Dong, Xiang Gao, Kamalika Das
2026	J	`jnl`	RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning. CoRR Xiang Gao, Yuguang Yao, Qi Zhang, Kaiwen Dong, Avinash Baidya, Ruocheng Guo, Hilaf Hasson, Kamalika Das
2026	A*	`conf`	Renormalization Group Guided Tensor Network Structure Search. AAAI Maolin Wang, Bowen Yu, Sheng Zhang, Linjie Mi, Wanyu Wang, Yiqi Wang, Pengyue Jia, Xuetao Wei, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
2026	A*	`conf`	SAGE: Global Semantic Alignment with LLMs for Long-Tail Sequential Recommendation. WWW Maolin Wang, Tongshu Bian, Ziyan Wang, Xiaotong Jiang, Binhao Wang, Derong Xu, Wanyu Wang, Ruocheng Guo, Xiangyu Zhao
2026	J	`jnl`	ToolPRMBench: Evaluating and Advancing Process Reward Models for Tool-using Agents. CoRR Dawei Li, Yuguang Yao, Zhen Tan, Huan Liu, Ruocheng Guo
2026	A	`conf`	Workshop on Benchmarking Causal Models (CausalBench). WSDM K. Selcuk Candan, Huan Liu, Ruocheng Guo, Paras Sheth
2025	B	`conf`	Confidence-Aware Fine-Tuning of Sequential Recommendation Systems Via Conformal Prediction. IEEE Big Data Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Philip S. Yu
2025	A*	`conf`	DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation. IJCAI Maolin Wang, Tianshuo Wei, Sheng Zhang, Ruocheng Guo, Wanyu Wang, Shanshan Ye, Lixin Zou, Xuetao Wei, Xiangyu Zhao
2025	J	`jnl`	DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation. CoRR Maolin Wang, Tianshuo Wei, Sheng Zhang, Ruocheng Guo, Wanyu Wang, Shanshan Ye, Lixin Zou, Xuetao Wei, Xiangyu Zhao
2025	J	`jnl`	Enhancing clinical documentation with voice processing and large language models: a study on the LAOS system. npj Digit. Medicine Yupeng Xu, Huixun Jia, Maolin Wang, Jie Feng, Xun Xu, Haiyan Wang, Jieqiong Chen, Zheng Zheng, Xiaoyan Yang, Yue Shen, Jian Wang, Chenyi Zhuang, Peng Wei, Ruocheng Guo, Xiangyu Zhao, Junxiang Fan, Xiaodong Sun
2025	—	`conf`	FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation. KDD (2) Maolin Wang, Yutian Xiao, Binhao Wang, Sheng Zhang, Shanshan Ye, Wanyu Wang, Hongzhi Yin, Ruocheng Guo, Zenglin Xu
2025	J	`jnl`	FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation. CoRR Maolin Wang, Yutian Xiao, Binhao Wang, Sheng Zhang, Shanshan Ye, Wanyu Wang, Hongzhi Yin, Ruocheng Guo, Zenglin Xu
2025	J	`jnl`	Identification and Estimation of Long-Term Treatment Effects with Monotone Missing. CoRR Qinwei Yang, Ruocheng Guo, Shasha Han, Peng Wu
2025	J	`jnl`	Learning Counterfactual Outcomes Under Rank Preservation. CoRR Peng Wu, Haoxuan Li, Chunyuan Zheng, Yan Zeng, Jiawei Chen, Yang Liu, Ruocheng Guo, Kun Zhang
2025	A*	`conf`	MetaLoRA: Tensor-Enhanced Adaptive Low-Rank Fine-Tuning. ICDE Maolin Wang, Xiangyu Zhao, Ruocheng Guo, Junhui Wang
2025	J	`jnl`	Node-Level Uncertainty Estimation in LLM-Generated SQL. CoRR Hilaf Hasson, Ruocheng Guo
2025	A*	`conf`	Optimal Policy Adaptation Under Covariate Shift. IJCAI Xueqing Liu, Qinwei Yang, Zhaoqing Tian, Ruocheng Guo, Peng Wu
2025	J	`jnl`	Optimal Policy Adaptation under Covariate Shift. CoRR Xueqing Liu, Qinwei Yang, Zhaoqing Tian, Ruocheng Guo, Peng Wu
2025	J	`jnl`	Renormalization Group Guided Tensor Network Structure Search. CoRR Maolin Wang, Bowen Yu, Sheng Zhang, Linjie Mi, Wanyu Wang, Yiqi Wang, Pengyue Jia, Xuetao Wei, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
2025	A	`conf`	SPARK: Adaptive Low-Rank Knowledge Graph Modeling in Hybrid Geometric Spaces for Recommendation. CIKM Binhao Wang, Yutian Xiao, Maolin Wang, Zhiqi Li, Tianshuo Wei, Ruocheng Guo, Xiangyu Zhao
2025	J	`jnl`	SPARK: Adaptive Low-Rank Knowledge Graph Modeling in Hybrid Geometric Spaces for Recommendation. CoRR Binhao Wang, Yutian Xiao, Maolin Wang, Zhiqi Li, Tianshuo Wei, Ruocheng Guo, Xiangyu Zhao
2025	A*	`conf`	STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation. SIGIR Maolin Wang, Sheng Zhang, Ruocheng Guo, Wanyu Wang, Xuetao Wei, Zitao Liu, Hongzhi Yin, Yi Chang, Xiangyu Zhao
2025	J	`jnl`	STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation. CoRR Maolin Wang, Sheng Zhang, Ruocheng Guo, Wanyu Wang, Xuetao Wei, Zitao Liu, Hongzhi Yin, Yi Chang, Xiangyu Zhao
2025	—	`conf`	Stepwise Reasoning Disruption Attack of LLMs. ACL (1) Jingyu Peng, Maolin Wang, Xiangyu Zhao, Kai Zhang, Wanyu Wang, Pengyue Jia, Qidong Liu, Ruocheng Guo, Qi Liu
2024	J	`jnl`	Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation. CoRR Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao
2024	J	`jnl`	Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction. CoRR Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu
2024	A*	`conf`	Conformal Counterfactual Inference under Hidden Confounding. KDD Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu
2024	J	`jnl`	Conformal Counterfactual Inference under Hidden Confounding. CoRR Zonghao Chen, Ruocheng Guo, Jean-François Ton, Yang Liu
2024	J	`jnl`	Cumulative Distribution Function based General Temporal Point Processes. CoRR Maolin Wang, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Zitao Liu, Langming Liu
2024	A	`conf`	DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems. RecSys Sheng Zhang, Maolin Wang, Xiangyu Zhao, Ruocheng Guo, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Zijian Zhang, Hongzhi Yin
2024	J	`jnl`	EASRec: Elastic Architecture Search for Efficient Long-term Sequential Recommender Systems. CoRR Sheng Zhang, Maolin Wang, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao, Zijian Zhang, Hongzhi Yin
2024	A*	`conf`	Fair Classifiers that Abstain without Harm. ICLR Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
2024	J	`jnl`	Large Language Models for Data Annotation: A Survey. CoRR Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu
2024	—	`conf`	Large Multimodal Model Compression via Iterative Efficient Pruning and Distillation. WWW (Companion Volume) Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao
2024	A*	`conf`	Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards. NeurIPS Qinwei Yang, Xueqing Liu, Yan Zeng, Ruocheng Guo, Yang Liu, Peng Wu
2024	B	`conf`	Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. DSAA Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu
2024	J	`jnl`	Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. CoRR Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu
2024	J	`jnl`	Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data. ACM Trans. Knowl. Discov. Data Qiang Huang, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang
2024	J	`jnl`	SMLP4Rec: An Efficient All-MLP Architecture for Sequential Recommendations. ACM Trans. Inf. Syst. Jingtong Gao, Xiangyu Zhao, Muyang Li, Minghao Zhao, Runze Wu, Ruocheng Guo, Yiding Liu, Dawei Yin
2024	J	`jnl`	Stepwise Reasoning Error Disruption Attack of LLMs. CoRR Jingyu Peng, Maolin Wang, Xiangyu Zhao, Kai Zhang, Wanyu Wang, Pengyue Jia, Qidong Liu, Ruocheng Guo, Qi Liu
2024	A	`conf`	Tensorized Hypergraph Neural Networks. SDM Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
2023	A*	`conf`	AutoMLP: Automated MLP for Sequential Recommendations. WWW Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo
2023	J	`jnl`	AutoMLP: Automated MLP for Sequential Recommendations. CoRR Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo
2023	J	`jnl`	Causal Disentanglement for Implicit Recommendations with Network Information. ACM Trans. Knowl. Discov. Data Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, Kasim Selçuk Candan
2023	A*	`conf`	Debiasing Recommendation by Learning Identifiable Latent Confounders. KDD Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
2023	J	`jnl`	Debiasing Recommendation by Learning Identifiable Latent Confounders. CoRR Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
2023	J	`jnl`	Deep Concept Removal. CoRR Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li
2023	J	`jnl`	Embedding in Recommender Systems: A Survey. CoRR Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, Ruocheng Guo
2023	A*	`conf`	Equal Opportunity of Coverage in Fair Regression. NeurIPS Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu
2023	J	`jnl`	Equal Opportunity of Coverage in Fair Regression. CoRR Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu
2023	J	`jnl`	Fair Classifiers that Abstain without Harm. CoRR Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
2023	J	`jnl`	Fair Learning to Rank with Distribution-free Risk Control. CoRR Ruocheng Guo, Jean-François Ton, Yang Liu
2023	A*	`conf`	Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. ICDM Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
2023	J	`jnl`	Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. CoRR Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
2023	A*	`conf`	Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. KDD Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang
2023	J	`jnl`	Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. CoRR Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang
2023	J	`jnl`	Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup. CoRR Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao
2023	A*	`conf`	Learning for Counterfactual Fairness from Observational Data. KDD Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
2023	J	`jnl`	Learning for Counterfactual Fairness from Observational Data. CoRR Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
2023	—	`conf`	Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. EMNLP (Findings) Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li
2023	J	`jnl`	Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. CoRR Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li
2023	J	`jnl`	Tensorized Hypergraph Neural Networks. CoRR Maolin Wang, Yaoming Zhen, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
2023	J	`jnl`	Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. CoRR Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li
2023	A*	`conf`	Virtual Node Tuning for Few-shot Node Classification. KDD Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
2023	J	`jnl`	Virtual Node Tuning for Few-shot Node Classification. CoRR Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
2023	—	`conf`	What Boosts Fake News Dissemination on Social Media? A Causal Inference View. PAKDD (4) Yichuan Li, Kyumin Lee, Nima Kordzadeh, Ruocheng Guo
2022	J	`jnl`	A Simple Yet Effective Pretraining Strategy for Graph Few-shot Learning. CoRR Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
2022	J	`jnl`	Accurate identification of bacteriophages from metagenomic data using Transformer. Briefings Bioinform. Jiayu Shang, Xubo Tang, Ruocheng Guo, Yanni Sun
2022	A*	`conf`	CLEAR: Generative Counterfactual Explanations on Graphs. NeurIPS Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
2022	J	`jnl`	CLEAR: Generative Counterfactual Explanations on Graphs. CoRR Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
2022	B	`conf`	Causal Disentanglement with Network Information for Debiased Recommendations. SISAP Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selçuk Candan, Huan Liu
2022	J	`jnl`	Causal Disentanglement with Network Information for Debiased Recommendations. CoRR Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, K. Selçuk Candan
2022	A	`conf`	Causal Mediation Analysis with Hidden Confounders. WSDM Lu Cheng, Ruocheng Guo, Huan Liu
2022	B	`conf`	Distributional Shift Adaptation using Domain-Specific Features. IEEE Big Data Anique Tahir, Lu Cheng, Ruocheng Guo, Huan Liu
2022	J	`jnl`	Distributional Shift Adaptation using Domain-Specific Features. CoRR Anique Tahir, Lu Cheng, Ruocheng Guo, Huan Liu
2022	A	`conf`	Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. ICWSM Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu
2022	A	`conf`	Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. WSDM Lu Cheng, Ruocheng Guo, Huan Liu
2022	J	`jnl`	Evaluation Methods and Measures for Causal Learning Algorithms. CoRR Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu
2022	J	`jnl`	Evaluation Methods and Measures for Causal Learning Algorithms. IEEE Trans. Artif. Intell. Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu
2022	A	`conf`	Graph Few-shot Class-incremental Learning. WSDM Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
2022	A	`conf`	Learning Fair Node Representations with Graph Counterfactual Fairness. WSDM Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
2022	J	`jnl`	Learning Fair Node Representations with Graph Counterfactual Fairness. CoRR Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
2022	A*	`conf`	MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. IJCAI Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo
2022	J	`jnl`	MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. CoRR Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo
2022	A*	`conf`	Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective. ICDM Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu
2022	J	`jnl`	Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective. CoRR Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu
2022	B	`conf`	Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. IEEE Big Data Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
2022	J	`jnl`	Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. CoRR Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
2022	—	`conf`	Supervised Graph Contrastive Learning for Few-Shot Node Classification. ECML/PKDD (2) Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
2021	J	`jnl`	A Survey of Learning Causality with Data: Problems and Methods. ACM Comput. Surv. Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu
2021	J	`jnl`	Adversarial Attacks and Defenses: An Interpretation Perspective. SIGKDD Explor. Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu
2021	J	`jnl`	Causal Mediation Analysis with Hidden Confounders. CoRR Lu Cheng, Ruocheng Guo, Huan Liu
2021	A*	`conf`	Causal Understanding of Fake News Dissemination on Social Media. KDD Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
2021	A	`conf`	CauseBox: A Causal Inference Toolbox for BenchmarkingTreatment Effect Estimators with Machine Learning Methods. CIKM Paras Sheth, Ujun Jeong, Ruocheng Guo, Huan Liu, K. Selçuk Candan
2021	A	`conf`	Deconfounding with Networked Observational Data in a Dynamic Environment. WSDM Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li
2021	J	`jnl`	Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. CoRR Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu
2021	J	`jnl`	Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. CoRR Lu Cheng, Ruocheng Guo, Huan Liu
2021	J	`jnl`	Graph Few-shot Class-incremental Learning. CoRR Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
2021	A	`conf`	Long-Term Effect Estimation with Surrogate Representation. WSDM Lu Cheng, Ruocheng Guo, Huan Liu
2021	J	`jnl`	Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks. Trans. Data Sci. Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu
2021	A*	`conf`	Multi-Cause Effect Estimation with Disentangled Confounder Representation. IJCAI Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
2021	J	`jnl`	Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix. CoRR Ruocheng Guo, Pengchuan Zhang, Hao Liu, Emre Kiciman
2020	J	`jnl`	Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. CoRR Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu
2020	J	`jnl`	Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. SIGKDD Explor. Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu
2020	A	`conf`	Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. SDM Ruocheng Guo, Jundong Li, Huan Liu
2020	A*	`conf`	Debiasing Grid-based Product Search in E-commerce. KDD Ruocheng Guo, Xiaoting Zhao, Adam Henderson, Liangjie Hong, Huan Liu
2020	A*	`conf`	IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data. IJCAI Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu
2020	A	`conf`	Learning Individual Causal Effects from Networked Observational Data. WSDM Ruocheng Guo, Jundong Li, Huan Liu
2020	J	`jnl`	Long-Term Effect Estimation with Surrogate Representation. CoRR Lu Cheng, Ruocheng Guo, Huan Liu
2020	J	`jnl`	Measuring Time-Constrained Influence to Predict Adoption in Online Social Networks. ACM Trans. Soc. Comput. Ericsson Marin, Ruocheng Guo, Paulo Shakarian
2020	A	`conf`	Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning. WSDM Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou, Huan Liu
2020	A	`conf`	Representation Learning for Imbalanced Cross-Domain Classification. SDM Lu Cheng, Ruocheng Guo, K. Selçuk Candan, Huan Liu
2020	J	`jnl`	Towards Causal Understanding of Fake News Dissemination. CoRR Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu
2019	—	`conf`	A Practical Data Repository for Causal Learning with Big Data. Bench Lu Cheng, Ruocheng Guo, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu
2019	A*	`conf`	Adaptive Unsupervised Feature Selection on Attributed Networks. KDD Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu
2019	—	`conf`	Causal Learning in Question Quality Improvement. Bench Yichuan Li, Ruocheng Guo, Weiying Wang, Huan Liu
2019	J	`jnl`	Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. CoRR Ruocheng Guo, Jundong Li, Huan Liu
2019	J	`jnl`	Detecting Pathogenic Social Media Accounts without Content or Network Structure. CoRR Elham Shaabani, Ruocheng Guo, Paulo Shakarian
2019	A	`conf`	Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network. SDM Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu
2019	J	`jnl`	I Am Not What I Write: Privacy Preserving Text Representation Learning. CoRR Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu
2019	J	`jnl`	Learning Individual Treatment Effects from Networked Observational Data. CoRR Ruocheng Guo, Jundong Li, Huan Liu
2019	B	`conf`	Multi-level network embedding with boosted low-rank matrix approximation. ASONAM Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, Huan Liu
2019	—	`conf`	Privacy Preserving Text Representation Learning. HT Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu
2019	J	`jnl`	Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning. CoRR Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou, Huan Liu
2019	A	`conf`	Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles. WSDM Ghazaleh Beigi, Ruocheng Guo, Alexander Nou, Yanchao Zhang, Huan Liu
2019	—	`conf`	Robust Cyberbullying Detection with Causal Interpretation. WWW (Companion Volume) Lu Cheng, Ruocheng Guo, Huan Liu
2019	J	`jnl`	Using network motifs to characterize temporal network evolution leading to diffusion inhibition. CoRR Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
2019	J	`jnl`	Using network motifs to characterize temporal network evolution leading to diffusion inhibition. Soc. Netw. Anal. Min. Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
2018	J	`jnl`	A Survey of Learning Causality with Data: Problems and Methods. CoRR Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu
2018	—	`conf`	Detecting Pathogenic Social Media Accounts without Content or Network Structure. ICDIS Elham Shaabani, Ruocheng Guo, Paulo Shakarian
2018	A*	`conf`	INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process. IJCAI Ruocheng Guo, Jundong Li, Huan Liu
2018	A	`conf`	Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects. CIKM Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu
2018	J	`jnl`	Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects. CoRR Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu
2018	J	`jnl`	Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles. CoRR Ghazaleh Beigi, Ruocheng Guo, Alexander Nou, Yanchao Zhang, Huan Liu
2018	A	`conf`	Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression. SDM Ruocheng Guo, Hamidreza Alvari, Paulo Shakarian
2018	J	`jnl`	Understanding and forecasting lifecycle events in information cascades. CoRR Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
2017	J	`jnl`	Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression. CoRR Ruocheng Guo, Hamidreza Alvari, Paulo Shakarian
2017	—	`conf`	Temporal Analysis of Influence to Predict Users' Adoption in Online Social Networks. SBP-BRiMS Ericsson Marin, Ruocheng Guo, Paulo Shakarian
2017	J	`jnl`	Temporal Analysis of Influence to Predict Users' Adoption in Online Social Networks. CoRR Ericsson Marin, Ruocheng Guo, Paulo Shakarian
2017	J	`jnl`	Understanding and forecasting lifecycle events in information cascades. Soc. Netw. Anal. Min. Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
2016	J	`jnl`	A Comparison of Methods for Cascade Prediction. CoRR Ruocheng Guo, Paulo Shakarian
2016	B	`conf`	A comparison of methods for cascade prediction. ASONAM Ruocheng Guo, Paulo Shakarian
2016	J	`jnl`	An Empirical Evaluation Of Social Influence Metrics. CoRR Nikhil Kumar, Ruocheng Guo, Ashkan Aleali, Paulo Shakarian
2016	B	`conf`	An empirical evaluation of social influence metrics. ASONAM Nikhil Kumar, Ruocheng Guo, Ashkan Aleali, Paulo Shakarian
2016	J	`jnl`	Toward Early and Order-of-Magnitude Cascade Prediction in Social Networks. CoRR Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian
2016	J	`jnl`	Toward early and order-of-magnitude cascade prediction in social networks. Soc. Netw. Anal. Min. Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian
2015	—	`book`	Diffusion in Social Networks Paulo Shakarian, Abhinav Bhatnagar, Ashkan Aleali, Elham Shaabani, Ruocheng Guo
2015	B	`conf`	Toward Order-of-Magnitude Cascade Prediction. ASONAM Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian
2015	J	`jnl`	Toward Order-of-Magnitude Cascade Prediction. CoRR Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian