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Rui Song 0006
Person information
- affiliation: North Carolina State University, North Carolina State University, Raleigh, NC, USA
- affiliation (PhD 2006): University of Wisconsin-Madison, WI, USA
Other persons with the same name
- Rui Song — disambiguation page
- Rui Song 0001 — Beijing Jiaotong University, School of Traffic and Transportation, China
- Rui Song 0002 — Shandong University, School of Control Science and Engineering, China
- Rui Song 0003 — Xidian University, State Key Laboratory of Integrated Service Networks, Xi'an, China (and 1 more)
- Rui Song 0004 — Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Science, Beijing, China
- Rui Song 0005 — University College London, Department of Mechanical Engineering, UK
- Rui Song 0007 — Technical University of Munich, TUM, Chair of Robotics, Artificial Intelligence and Real-time Systems, Garching, Germany (and 1 more)
- Rui Song 0008 — Jilin University, School of Artificial Intelligence, Changchun, China
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2020 – today
- 2024
- [j13]Jingping Liu, Lihan Chen, Sihang Jiang, Chao Wang, Sheng Zhang, Jiaqing Liang, Yanghua Xiao, Rui Song:
A crossword solving system based on Monte Carlo tree search. Artif. Intell. 335: 104192 (2024) - [c25]Yu Liu, Runzhe Wan, James McQueen, Doug Hains, Jinxiang Gu, Rui Song:
Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches. AAAI 2024: 14044-14051 - [i42]Hengrui Cai, Shengjie Liu, Rui Song:
Is Knowledge All Large Language Models Needed for Causal Reasoning? CoRR abs/2401.00139 (2024) - [i41]Lin Ge, Yang Xu, Jianing Chu, David Cramer, Fuhong Li, Kelly Paulson, Rui Song:
Multi-Task Combinatorial Bandits for Budget Allocation. CoRR abs/2409.00561 (2024) - [i40]Yang Xu, Wenbin Lu, Rui Song:
Linear Contextual Bandits with Interference. CoRR abs/2409.15682 (2024) - [i39]Branislav Kveton, Boris Oreshkin, Youngsuk Park, Aniket Deshmukh, Rui Song:
Online Posterior Sampling with a Diffusion Prior. CoRR abs/2410.03919 (2024) - 2023
- [j12]Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu:
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments. J. Mach. Learn. Res. 24: 140:1-140:92 (2023) - [c24]Runzhe Wan, Lin Ge, Rui Song:
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. AISTATS 2023: 1144-1173 - [c23]Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song:
A Reinforcement Learning Framework for Dynamic Mediation Analysis. ICML 2023: 11050-11097 - [c22]Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song:
Multiplier Bootstrap-based Exploration. ICML 2023: 35444-35490 - [c21]Richard A. Watson, Hengrui Cai, Xinming An, Samuel A. McLean, Rui Song:
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs. ICML 2023: 36714-36747 - [c20]Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song:
An Instrumental Variable Approach to Confounded Off-Policy Evaluation. ICML 2023: 38848-38880 - [c19]Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song:
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. KDD 2023: 5016-5027 - [c18]Zhiwei (Tony) Qin, Rui Song, Jieping Ye, Hongtu Zhu, Michael I. Jordan:
KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces. KDD 2023: 5878-5879 - [c17]Hengrui Cai, Yixin Wang, Michael I. Jordan, Rui Song:
On Learning Necessary and Sufficient Causal Graphs. NeurIPS 2023 - [i38]Yuhe Gao, Chengchun Shi, Rui Song:
Deep Spectral Q-learning with Application to Mobile Health. CoRR abs/2301.00927 (2023) - [i37]Richard A. Watson, Hengrui Cai, Xinming An, Samuel A. McLean, Rui Song:
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs. CoRR abs/2301.12383 (2023) - [i36]Hengrui Cai, Yixin Wang, Michael I. Jordan, Rui Song:
On Learning Necessary and Sufficient Causal Graphs. CoRR abs/2301.12389 (2023) - [i35]Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song:
A Reinforcement Learning Framework for Dynamic Mediation Analysis. CoRR abs/2301.13348 (2023) - [i34]Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song:
Multiplier Bootstrap-based Exploration. CoRR abs/2302.01543 (2023) - [i33]Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song:
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. CoRR abs/2304.00420 (2023) - [i32]Yu Liu, Runzhe Wan, James McQueen, Doug Hains, Jinxiang Gu, Rui Song:
Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches. CoRR abs/2312.12871 (2023) - [i31]Haoyu Wei, Runzhe Wan, Lei Shi, Rui Song:
Zero-Inflated Bandits. CoRR abs/2312.15595 (2023) - [i30]Haitao Jiang, Lin Ge, Yuhe Gao, Jianian Wang, Rui Song:
Large Language Model for Causal Decision Making. CoRR abs/2312.17122 (2023) - 2022
- [j11]Ye Liu, Rui Song, Wenbin Lu, Yanghua Xiao:
A Probit Tensor Factorization Model For Relational Learning. J. Comput. Graph. Stat. 31(3): 846-855 (2022) - [j10]Lihan Chen, Sihang Jiang, Jingping Liu, Chao Wang, Sheng Zhang, Chenhao Xie, Jiaqing Liang, Yanghua Xiao, Rui Song:
Rule mining over knowledge graphs via reinforcement learning. Knowl. Based Syst. 242: 108371 (2022) - [j9]Wenbo Pu, Jing Hu, Xin Wang, Yuezun Li, Shu Hu, Bin Zhu, Rui Song, Qi Song, Xi Wu, Siwei Lyu:
Learning a deep dual-level network for robust DeepFake detection. Pattern Recognit. 130: 108832 (2022) - [j8]Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond. SIGKDD Explor. 24(2): 78-80 (2022) - [c16]Lihan Chen, Jingping Liu, Sihang Jiang, Chao Wang, Jiaqing Liang, Yanghua Xiao, Sheng Zhang, Rui Song:
Crossword Puzzle Resolution via Monte Carlo Tree Search. ICAPS 2022: 35-43 - [c15]Runzhe Wan, Branislav Kveton, Rui Song:
Safe Exploration for Efficient Policy Evaluation and Comparison. ICML 2022: 22491-22511 - [c14]Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond. KDD 2022: 4898-4899 - [i29]Elynn Y. Chen, Rui Song, Michael I. Jordan:
Reinforcement Learning with Heterogeneous Data: Estimation and Inference. CoRR abs/2202.00088 (2022) - [i28]Lihan Chen, Sihang Jiang, Jingping Liu, Chao Wang, Sheng Zhang, Chenhao Xie, Jiaqing Liang, Yanghua Xiao, Rui Song:
Rule Mining over Knowledge Graphs via Reinforcement Learning. CoRR abs/2202.10381 (2022) - [i27]Chengchun Shi, Runzhe Wan, Ge Song, Shikai Luo, Rui Song, Hongtu Zhu:
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets. CoRR abs/2202.10574 (2022) - [i26]Chengchun Shi, Jin Zhu, Ye Shen, Shikai Luo, Hongtu Zhu, Rui Song:
Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process. CoRR abs/2202.10589 (2022) - [i25]Haoyu Chen, Wenbin Lu, Rui Song, Pulak Ghosh:
On Learning and Testing of Counterfactual Fairness through Data Preprocessing. CoRR abs/2202.12440 (2022) - [i24]Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song:
Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons. CoRR abs/2202.13163 (2022) - [i23]Runzhe Wan, Lin Ge, Rui Song:
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. CoRR abs/2202.13227 (2022) - [i22]Runzhe Wan, Branislav Kveton, Rui Song:
Safe Exploration for Efficient Policy Evaluation and Comparison. CoRR abs/2202.13234 (2022) - [i21]Runzhe Wan, Yingying Li, Wenbin Lu, Rui Song:
Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies. CoRR abs/2212.12845 (2022) - [i20]Yang Xu, Chengchun Shi, Shikai Luo, Lan Wang, Rui Song:
Quantile Off-Policy Evaluation via Deep Conditional Generative Learning. CoRR abs/2212.14466 (2022) - [i19]Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song:
An Instrumental Variable Approach to Confounded Off-Policy Evaluation. CoRR abs/2212.14468 (2022) - [i18]Ye Shen, Runzhe Wan, Hengrui Cai, Rui Song:
Heterogeneous Synthetic Learner for Panel Data. CoRR abs/2212.14580 (2022) - 2021
- [j7]Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song:
An Online Sequential Test for Qualitative Treatment Effects. J. Mach. Learn. Res. 22: 286:1-286:51 (2021) - [c13]Miao Yu, Wenbin Lu, Rui Song:
Online Testing of Subgroup Treatment Effects Based on Value Difference. ICDM 2021: 1463-1468 - [c12]Hengrui Cai, Rui Song, Wenbin Lu:
ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning. ICLR 2021 - [c11]Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song:
Deeply-Debiased Off-Policy Interval Estimation. ICML 2021: 9580-9591 - [c10]Runzhe Wan, Xinyu Zhang, Rui Song:
Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control. KDD 2021: 1634-1644 - [c9]Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu:
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. NeurIPS 2021: 15285-15300 - [c8]Runzhe Wan, Lin Ge, Rui Song:
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models. NeurIPS 2021: 29655-29668 - [i17]Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song:
Deeply-Debiased Off-Policy Interval Estimation. CoRR abs/2105.04646 (2021) - [i16]Runzhe Wan, Sheng Zhang, Chengchun Shi, Shikai Luo, Rui Song:
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching. CoRR abs/2105.13218 (2021) - [i15]Hengrui Cai, Zhihao Cen, Ling Leng, Rui Song:
Periodic-GP: Learning Periodic World with Gaussian Process Bandits. CoRR abs/2105.14422 (2021) - [i14]Runzhe Wan, Lin Ge, Rui Song:
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models. CoRR abs/2108.06422 (2021) - [i13]Hengrui Cai, Ye Shen, Rui Song:
Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning. CoRR abs/2110.15501 (2021) - [i12]Ye Liu, Rui Song, Wenbin Lu, Yanghua Xiao:
A Probit Tensor Factorization Model For Relational Learning. CoRR abs/2111.03943 (2021) - [i11]Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu:
Jump Interval-Learning for Individualized Decision Making. CoRR abs/2111.08885 (2021) - [i10]Jianian Wang, Sheng Zhang, Yanghua Xiao, Rui Song:
A Review on Graph Neural Network Methods in Financial Applications. CoRR abs/2111.15367 (2021) - 2020
- [j6]Chengchun Shi, Wenbin Lu, Rui Song:
Breaking the Curse of Nonregularity with Subagging - Inference of the Mean Outcome under Optimal Treatment Regimes. J. Mach. Learn. Res. 21: 176:1-176:67 (2020) - [j5]Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou, Zhenming Liu, Rui Song, Hui Lu, Zhihong Tian, Jun Luo:
DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers' Learning Curve Analysis. ACM Trans. Intell. Syst. Technol. 11(1): 8:1-8:19 (2020) - [c7]Miao Yu, Wenbin Lu, Rui Song:
A New Framework for Online Testing of Heterogeneous Treatment Effect. AAAI 2020: 10310-10317 - [c6]Ye Liu, Sheng Zhang, Rui Song, Suo Feng, Yanghua Xiao:
Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning. EMNLP (1) 2020: 8595-8604 - [c5]Hengrui Cai, Wenbin Lu, Rui Song:
On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies. ICML 2020: 1262-1270 - [c4]Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng:
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. ICML 2020: 8807-8817 - [c3]Liangyu Zhu, Wenbin Lu, Rui Song:
Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health. ICML 2020: 11588-11598 - [c2]Liangyu Zhu, Wenbin Lu, Michael R. Kosorok, Rui Song:
Kernel Assisted Learning for Personalized Dose Finding. KDD 2020: 56-65 - [i9]Chengchun Shi, Sheng Zhang, Wenbin Lu, Rui Song:
Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings. CoRR abs/2001.04515 (2020) - [i8]Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye:
A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. CoRR abs/2002.01711 (2020) - [i7]Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng:
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. CoRR abs/2002.01751 (2020) - [i6]Runzhe Wan, Xinyu Zhang, Rui Song:
Multi-Objective Reinforcement Learning for Infectious Disease Control with Application to COVID-19 Spread. CoRR abs/2009.04607 (2020) - [i5]Haoyu Chen, Wenbin Lu, Rui Song:
Statistical Inference for Online Decision-Making: In a Contextual Bandit Setting. CoRR abs/2010.07283 (2020) - [i4]Haoyu Chen, Wenbin Lu, Rui Song:
Statistical Inference for Online Decision Making via Stochastic Gradient Descent. CoRR abs/2010.07341 (2020) - [i3]Ye Liu, Sheng Zhang, Rui Song, Suo Feng, Yanghua Xiao:
Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning. CoRR abs/2010.09189 (2020) - [i2]Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu:
Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space. CoRR abs/2010.15963 (2020)
2010 – 2019
- 2019
- [j4]Chengchun Shi, Wenbin Lu, Rui Song:
Determining the Number of Latent Factors in Statistical Multi-Relational Learning. J. Mach. Learn. Res. 20: 23:1-23:38 (2019) - [c1]Menghai Pan, Yanhua Li, Xun Zhou, Zhenming Liu, Rui Song, Hui Lu, Jun Luo:
Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach. SDM 2019: 783-791 - 2017
- [j3]Zhongkai Liu, Rui Song, Donglin Zeng, Jiajia Zhang:
Principal components adjusted variable screening. Comput. Stat. Data Anal. 110: 134-144 (2017) - [j2]Shuhan Liang, Wenbin Lu, Rui Song, Lan Wang:
Sparse Concordance-assisted Learning for Optimal Treatment Decision. J. Mach. Learn. Res. 18: 202:1-202:26 (2017) - 2014
- [i1]Shikai Luo, Rui Song, Daniela M. Witten:
Sure Screening for Gaussian Graphical Models. CoRR abs/1407.7819 (2014) - 2012
- [j1]Rui Song, Jian Huang, Shuangge Ma:
Integrative prescreening in analysis of multiple cancer genomic studies. BMC Bioinform. 13: 168 (2012)
Coauthor Index
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last updated on 2024-12-11 20:37 CET by the dblp team
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