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ORCIDHaoxuan Li 0001
Person information
- unicode name: 李昊轩
- affiliation: Peking University, Beijing, China
Other persons with the same name
- Haoxuan Li (aka: Hao-Xuan Li) — disambiguation page
- Haoxuan Li 0002
![[0009-0005-1355-6256]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0009-0005-1355-6256")
— University of Electronic Science and Technology of China, Chengdu, China - Haoxuan Li 0003 — Beihang University, Beijing, China
- Haoxuan Li 0004 — Shanghai Jiao Tong University, Shanghai, China
- Haoxuan Li 0005 — Technical University of Munich, Garching, Germany
- Haoxuan Li 0006 — University of International Business and Economics, Beijing, China
- Haoxuan Li 0007 — University of Science and Technology Beijing, Beijing, China
- Haoxuan Li 0008 — Huazhong University of Science and Technology, China
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2020 – today
- 2025
[j1]Hao Wang, Zhichao Chen, Zhaoran Liu, Haozhe Li, Degui Yang, Xinggao Liu, Haoxuan Li:
Entire Space Counterfactual Learning for Reliable Content Recommendations. IEEE Trans. Inf. Forensics Secur. 20: 1755-1764 (2025)- [c37]Guorui Liao, Chunyuan Zheng, Li Cheng, Haoyu Xie, Shanshan Huang, Jun Liao, Haoxuan Li, Li Liu:
HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units. AAAI 2025: 14309-14317 - [c36]Haotian Wang, Haoxuan Li, Hao Zou, Haoang Chi, Long Lan, Wanrong Huang, Wenjing Yang:
Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. ICLR 2025 - [c35]Hao Wang, Lichen Pan, Yuan Shen, Zhichao Chen, Degui Yang, Yifei Yang, Sen Zhang, Xinggao Liu, Haoxuan Li, Dacheng Tao:
FreDF: Learning to Forecast in the Frequency Domain. ICLR 2025 - [c34]Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, BinChen, Zhichao Chen:
Optimal Transport for Time Series Imputation. ICLR 2025 - [c33]Anpeng Wu, Haoxuan Li, Chunyuan Zheng, Kun Kuang, Kun Zhang:
Classifying Treatment Responders: Bounds and Algorithms. KDD (1) 2025: 1611-1622 - [c32]Chuan Zhou, Yaxuan Li, Chunyuan Zheng, Haiteng Zhang, Min Zhang, Haoxuan Li, Mingming Gong:
A Two-Stage Pretraining-Finetuning Framework for Treatment Effect Estimation with Unmeasured Confounding. KDD (1) 2025: 2113-2123 - [c31]Lei Wang, Jianxun Lian, Yi Huang, Yanqi Dai, Haoxuan Li, Xu Chen, Xing Xie, Ji-Rong Wen:
CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds. NAACL (Long Papers) 2025: 6372-6391 - [c30]Huayi Yang, Chunyuan Zheng, Guorui Liao, Shanshan Huang, Jun Liao, Zhili Gong, Haoxuan Li, Li Liu:
CAP: Causal Air Quality Index Prediction Under Interference with Unmeasured Confounding. WWW 2025: 5320-5329 - 2024
- [c29]Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang:
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. AAAI 2024: 17175-17183 - [c28]Honglei Zhang, Shuyi Wang, Haoxuan Li, Chunyuan Zheng, Xu Chen, Li Liu, Shanshan Luo, Peng Wu:
Uncovering the Propensity Identification Problem in Debiased Recommendations. ICDE 2024: 653-666 - [c27]Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He:
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. ICLR 2024 - [c26]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. ICLR 2024 - [c25]Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang:
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. ICLR 2024 - [c24]Jinqiu Jin, Haoxuan Li, Fuli Feng:
On the Maximal Local Disparity of Fairness-Aware Classifiers. ICML 2024 - [c23]Baohong Li, Haoxuan Li, Anpeng Wu, Minqin Zhu, Shiyuan Peng, Qingyu Cao, Kun Kuang:
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective. ICML 2024 - [c22]Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu, Kun Kuang:
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. ICML 2024 - [c21]Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Eric Hao Wang, Peng Wu, Zhi Geng, Xu Chen, Xiao-Hua Zhou:
Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering. ICML 2024 - [c20]Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu:
Learning Causal Relations from Subsampled Time Series with Two Time-Slices. ICML 2024 - [c19]Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou:
Debiased Recommendation with Noisy Feedback. KDD 2024: 1576-1586 - [c18]Wenjing Yang, Haotian Wang, Haoxuan Li, Hao Zou, Ruochun Jin, Kun Kuang, Peng Cui:
Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. KDD 2024: 3829-3840 - [c17]Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Hao Wang:
Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective. NeurIPS 2024 - [i28]Honglei Zhang, He Liu, Haoxuan Li, Yidong Li:
TransFR: Transferable Federated Recommendation with Pre-trained Language Models. CoRR abs/2402.01124 (2024) - [i27]Hao Wang, Licheng Pan, Zhichao Chen, Degui Yang, Sen Zhang, Yifei Yang, Xinggao Liu, Haoxuan Li, Dacheng Tao:
FreDF: Learning to Forecast in Frequency Domain. CoRR abs/2402.02399 (2024) - [i26]Jun Wang, Haoxuan Li, Chi Zhang, Dongxu Liang, Enyun Yu, Wenwu Ou, Wenjia Wang:
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation. CoRR abs/2402.05740 (2024) - [i25]Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang:
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. CoRR abs/2403.02624 (2024) - [i24]Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang:
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. CoRR abs/2403.14232 (2024) - [i23]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. CoRR abs/2404.19596 (2024) - [i22]Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He:
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. CoRR abs/2404.19620 (2024) - [i21]Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang:
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. CoRR abs/2404.19644 (2024) - [i20]Anjie Liu, Jianhong Wang, Haoxuan Li, Xu Chen, Jun Wang, Samuel Kaski, Mengyue Yang:
Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games. CoRR abs/2405.16588 (2024) - [i19]Jinqiu Jin, Haoxuan Li, Fuli Feng:
On the Maximal Local Disparity of Fairness-Aware Classifiers. CoRR abs/2406.03255 (2024) - [i18]Honglei Zhang, Haoxuan Li, Jundong Chen, Sen Cui, Kunda Yan, Abudukelimu Wuerkaixi, Xin Zhou, Zhiqi Shen, Yidong Li:
Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation. CoRR abs/2406.03933 (2024) - [i17]Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Eric H. Wang:
Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow. CoRR abs/2406.15762 (2024) - [i16]Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou:
Debiased Recommendation with Noisy Feedback. CoRR abs/2406.17182 (2024) - [i15]Hao Wang, Zhichao Chen, Yuan Shen, Jiajun Fan, Zhaoran Liu, Degui Yang, Xinggao Liu, Haoxuan Li:
Proximity Matters: Local Proximity Preserved Balancing for Treatment Effect Estimation. CoRR abs/2407.01111 (2024) - [i14]Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Ruoxuan Xiong, Fei Wu, Kun Kuang:
Causal Inference with Complex Treatments: A Survey. CoRR abs/2407.14022 (2024) - [i13]Hang Pan, Shuxian Bi, Wenjie Wang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He:
Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence. CoRR abs/2409.08934 (2024) - [i12]Zhengnan Li, Haoxuan Li, Hao Wang, Jun Fang, Duoyin Li, Yunxiao Qin:
FSMLP: Modelling Channel Dependencies With Simplex Theory Based Multi-Layer Perceptions In Frequency Domain. CoRR abs/2412.01654 (2024) - [i11]Lei Wang, Jianxun Lian, Yi Huang, Yanqi Dai, Haoxuan Li, Xu Chen, Xing Xie, Ji-Rong Wen:
CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds. CoRR abs/2412.05631 (2024) - 2023
- [c16]Haoxuan Li, Quanyu Dai, Yuru Li, Yan Lyu, Zhenhua Dong, Xiao-Hua Zhou, Peng Wu:
Multiple Robust Learning for Recommendation. AAAI 2023: 4417-4425 - [c15]Jun Wang, Haoxuan Li, Chi Zhang, Dongxu Liang, Enyun Yu, Wenwu Ou, Wenjia Wang:
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation. ICDM 2023: 1355-1360 - [c14]Haoxuan Li, Yan Lyu, Chunyuan Zheng, Peng Wu:
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. ICLR 2023 - [c13]Haoxuan Li, Chunyuan Zheng, Peng Wu:
StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. ICLR 2023 - [c12]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, Peng Cui:
Propensity Matters: Measuring and Enhancing Balancing for Recommendation. ICML 2023: 20182-20194 - [c11]Haoxuan Li, Chunyuan Zheng, Yixiao Cao, Zhi Geng, Yue Liu, Peng Wu:
Trustworthy Policy Learning under the Counterfactual No-Harm Criterion. ICML 2023: 20575-20598 - [c10]Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui:
Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. KDD 2023: 1235-1247 - [c9]Shanshan Huang, Haoxuan Li, Qingsong Li, Chunyuan Zheng, Li Liu:
Pareto Invariant Representation Learning for Multimedia Recommendation. ACM Multimedia 2023: 6410-6419 - [c8]Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu, Xiangnan He:
Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. NeurIPS 2023 - [c7]Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu:
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. NeurIPS 2023 - [c6]Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. NeurIPS 2023 - [c5]Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou:
ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. RecSys 2023: 682-687 - [c4]Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He:
Causal Recommendation: Progresses and Future Directions. SIGIR 2023: 3432-3435 - [c3]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu:
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. WWW 2023: 1305-1313 - [i10]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu:
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. CoRR abs/2304.09085 (2023) - [i9]Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou:
ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. CoRR abs/2308.02571 (2023) - [i8]Hao Wang, Jianxun Lian, Mingqi Wu, Haoxuan Li, Jiajun Fan, Wanyue Xu, Chaozhuo Li, Xing Xie:
ConvFormer: Revisiting Transformer for Sequential User Modeling. CoRR abs/2308.02925 (2023) - [i7]Shanshan Huang, Haoxuan Li, Qingsong Li, Chunyuan Zheng, Li Liu:
Pareto Invariant Representation Learning for Multimedia Recommendation. CoRR abs/2308.04706 (2023) - [i6]Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu:
Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series. CoRR abs/2308.08148 (2023) - [i5]Hao Wang, Zhichao Chen, Jiajun Fan, Haoxuan Li, Tianqiao Liu, Weiming Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. CoRR abs/2310.18286 (2023) - 2022
- [c2]Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou:
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. IJCAI 2022: 5646-5653 - [c1]Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. KDD 2022: 252-262 - [i4]Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou:
Causal Analysis Framework for Recommendation. CoRR abs/2201.06716 (2022) - [i3]Peng Wu, Haoxuan Li, Yan Lyu, Xiao-Hua Zhou:
Doubly Robust Collaborative Targeted Learning for Recommendation on Data Missing Not at Random. CoRR abs/2203.10258 (2022) - [i2]Haoxuan Li, Chunyuan Zheng, Xiao-Hua Zhou, Peng Wu:
Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. CoRR abs/2205.04701 (2022) - [i1]Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. CoRR abs/2211.06684 (2022)
Coauthor Index
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