Hao Zou - RankMe

38 papers A* 19Journal 15Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Detecting Unobserved Confounders: A Kernelized Regression Approach. AAAI Yikai Chen, Yunxin Mao, Chunyuan Zheng, Hao Zou, Shanzhi Gu, Shixuan Liu, Yang Shi, Wenjing Yang, Kun Kuang, Haotian Wang
2026	J	`jnl`	Detecting Unobserved Confounders: A Kernelized Regression Approach. CoRR Yikai Chen, Yunxin Mao, Chunyuan Zheng, Hao Zou, Shanzhi Gu, Shixuan Liu, Yang Shi, Wenjing Yang, Kun Kuang, Haotian Wang
2026	A*	`conf`	Error Slice Discovery via Manifold Compactness. AAAI Han Yu, Hao Zou, Jiashuo Liu, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui
2026	A*	`conf`	Generating Risky Samples with Conformity Constraints via Diffusion Models. AAAI Han Yu, Hao Zou, Xingxuan Zhang, Zhengyi Wang, Yue He, Kehan Li, Peng Cui
2026	A*	`conf`	Invariant Learning on Heterogeneous Graphs via Subgraph Environment Inference. WWW Yanghui Fu, Yunfei Wang, Hao Zou, Yue He, Haotian Wang, Qing Cheng, Guangquan Cheng, Shixuan Liu
2026	A*	`conf`	Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents. AAAI Xinpeng Lv, Chunyuan Zheng, Yunxin Mao, Renzhe Xu, Hao Zou, Shanzhi Gu, Liyang Xu, Huan Chen, Yuanlong Chen, Wenjing Yang, Haotian Wang
2025	J	`jnl`	AdaptSel: Adaptive Selection of Biased and Debiased Recommendation Models for Varying Test Environments. ACM Trans. Knowl. Discov. Data Zimu Wang, Hao Zou, Jiashuo Liu, Jiayun Wu, Pengfei Tian, Yue He, Peng Cui
2025	A*	`conf`	COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. CVPR Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui
2025	J	`jnl`	COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. CoRR Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui
2025	A*	`conf`	Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. ICLR Haotian Wang, Haoxuan Li, Hao Zou, Haoang Chi, Long Lan, Wanrong Huang, Wenjing Yang
2025	J	`jnl`	Error Slice Discovery via Manifold Compactness. CoRR Han Yu, Jiashuo Liu, Hao Zou, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui
2025	J	`jnl`	Exploring and Exploiting Data Heterogeneity in Recommendation. ACM Trans. Knowl. Discov. Data Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui
2025	J	`jnl`	Generating Risky Samples with Conformity Constraints via Diffusion Models. CoRR Han Yu, Hao Zou, Xingxuan Zhang, Zhengyi Wang, Yue He, Kehan Li, Peng Cui
2025	A*	`conf`	Learning Feasible Causal Algorithmic Recourse: A Prior Structural Knowledge Free Approach. WWW Haotian Wang, Hao Zou, Xueguang Zhou, Shangwen Wang, Wenjing Yang, Peng Cui
2025	J	`jnl`	LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence. CoRR Xingxuan Zhang, Gang Ren, Han Yu, Hao Yuan, Hui Wang, Jiansheng Li, Jiayun Wu, Lang Mo, Li Mao, Mingchao Hao, Ningbo Dai, Renzhe Xu, Shuyang Li, Tianyang Zhang, Yue He, Yuanrui Wang, Yunjia Zhang, Zijing Xu, Dongzhe Li, Fang Gao, Hao Zou, Jiandong Liu, Jiashuo Liu, Jiawei Xu, Kaijie Cheng, Kehan Li, Linjun Zhou, Qing Li, Shaohua Fan, Xiaoyu Lin, Xinyan Han, Xuanyue Li, Yan Lu, Yuan Xue, Yuanyuan Jiang, Zimu Wang, Zhenlei Wang, Peng Cui
2025	—	`conf`	PDMC: Generating Feasible Algorithmic Recourse via Perturbation Data Manifold Constraint. KDD (2) Zimu Wang, Hao Zou, Han Yu, Shaohua Fan, Haotian Wang, Yue He, Peng Cui
2025	J	`jnl`	Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift. CoRR Shixuan Liu, Yue He, Yunfei Wang, Hao Zou, Haoxiang Cheng, Wenjing Yang, Peng Cui, Zhong Liu
2025	A*	`conf`	Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. ICLR Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui
2025	J	`jnl`	Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. CoRR Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui
2024	A*	`conf`	Domain-wise Data Acquisition to Improve Performance under Distribution Shift. ICML Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu, Hao Zou, Peng Cui
2024	A*	`conf`	Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. ICML Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui
2024	—	`conf`	Learning Feasible Causal Algorithmic Recourse without Prior Structure. ICDM (Workshops) Haotian Wang, Hao Zou, Xueguang Zhou, Shangwen Wang, Long Lan, Wenjing Yang, Peng Cui
2024	A*	`conf`	Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. KDD Wenjing Yang, Haotian Wang, Haoxuan Li, Hao Zou, Ruochun Jin, Kun Kuang, Peng Cui
2023	J	`jnl`	Exploring and Exploiting Data Heterogeneity in Recommendation. CoRR Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui
2023	—	`conf`	Factual Observation Based Heterogeneity Learning for Counterfactual Prediction. CLeaR Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui
2023	J	`jnl`	Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. CoRR Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui
2023	A*	`conf`	Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CVPR Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui
2023	J	`jnl`	Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CoRR Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui
2023	A*	`conf`	Offline Policy Evaluation in Large Action Spaces via Outcome-Oriented Action Grouping. WWW Jie Peng, Hao Zou, Jiashuo Liu, Shaoming Li, Yibao Jiang, Jian Pei, Peng Cui
2022	A*	`conf`	CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. WWW Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang
2022	J	`jnl`	CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. CoRR Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang
2022	A*	`conf`	Counterfactual Prediction for Outcome-Oriented Treatments. ICML Hao Zou, Bo Li, Jiangang Han, Shuiping Chen, Xuetao Ding, Peng Cui
2022	J	`jnl`	Data-Driven Variable Decomposition for Treatment Effect Estimation. IEEE Trans. Knowl. Data Eng. Kun Kuang, Peng Cui, Hao Zou, Bo Li, Jianrong Tao, Fei Wu, Shiqiang Yang
2020	A*	`conf`	Counterfactual Prediction for Bundle Treatment. NeurIPS Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He
2020	A*	`conf`	Learning Stable Graphs from Multiple Environments with Selection Bias. KDD Yue He, Peng Cui, Jianxin Ma, Hao Zou, Xiaowei Wang, Hongxia Yang, Philip S. Yu
2019	—	`conf`	Causation-Driven Visualizations for Insurance Recommendation. ICME Workshops Zhixiu Liu, Chengxi Zang, Kun Kuang, Hao Zou, Hu Zheng, Peng Cui
2019	A*	`conf`	Focused Context Balancing for Robust Offline Policy Evaluation. KDD Hao Zou, Kun Kuang, Boqi Chen, Peixuan Chen, Peng Cui
2018	J	`jnl`	Physical Co-Design of Flow and Control Layers for Flow-Based Microfluidic Biochips. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Qin Wang, Hao Zou, Hailong Yao, Tsung-Yi Ho, Robert Wille, Yici Cai