ML Anthology

Ma, Yao

24 publications

NeurIPS 2025 Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking Liangliang Zhang, Zhuorui Jiang, Hongliang Chi, Haoyang Chen, Mohammed ElKoumy, Fali Wang, Qiong Wu, Zhengyi Zhou, Shirui Pan, Suhang Wang, Yao Ma
LoG 2025 Do Neural Scaling Laws Exist on Graph Self-Supervised Learning? Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma
TMLR 2025 Extending Graph Condensation to Multi-Label Datasets: A Benchmark Study Liangliang Zhang, Haoran Bao, Yao Ma
NeurIPS 2025 Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve Yuanzhe Liu, Ryan Deng, Tim Kaler, Xuhao Chen, Charles Leiserson, Yao Ma, Jie Chen
ICLR 2025 Precedence-Constrained Winter Value for Effective Graph Data Valuation Hongliang Chi, Wei Jin, Charu C. Aggarwal, Yao Ma
ICLR 2025 Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation Hongliang Chi, Qiong Wu, Zhengyi Zhou, Yao Ma
NeurIPS 2025 Understanding and Enhancing Message Passing on Heterophilic Graphs via Compatibility Matrix Zhuonan Zheng, Yuanchen Bei, Zhiyao Zhou, Sheng Zhou, Yao Ma, Ming Gu, Hongjia Xu, Jiawei Chen, Jiajun Bu
CoLLAs 2024 Gradual Fine-Tuning with Graph Routing for Multi-Source Unsupervised Domain Adaptation Yao Ma, Samuel Louvan, Zhunxuan Wang
ICML 2024 PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Haitao Mao, Qian Chen, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun
ICML 2024 Position: Graph Foundation Models Are Already Here Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
ICLR 2024 Revisiting Link Prediction: A Data Perspective Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
ICMLW 2024 Structure-Based Drug Design Benchmark: Do 3D Methods Really Dominate? Kangyu Zheng, Yingzhou Lu, Zaixi Zhang, Zhongwei Wan, Yao Ma, Marinka Zitnik, Tianfan Fu
NeurIPS 2023 Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
NeurIPS 2023 Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
ICLR 2022 Automated Self-Supervised Learning for Graphs Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
ICLR 2022 Is Homophily a Necessity for Graph Neural Networks? Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
ICML 2021 Elastic Graph Neural Networks Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
NeurIPS 2021 Graph Neural Networks with Adaptive Residual Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang
JMLR 2020 Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers Yao Ma, Alex Olshevsky, Csaba Szepesvari, Venkatesh Saligrama
ICLR 2020 R-Transformer: Recurrent Neural Network Enhanced Transformer Zhiwei Wang, Yao Ma, Zitao Liu, Jiliang Tang
IJCAI 2019 Deep Adversarial Social Recommendation Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li
ICML 2018 Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers Yao Ma, Alexander Olshevsky, Csaba Szepesvari, Venkatesh Saligrama
NeurIPS 2016 Theoretical Comparisons of Positive-Unlabeled Learning Against Positive-Negative Learning Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Yao Ma, Masashi Sugiyama
ECML-PKDD 2014 An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions Yao Ma, Tingting Zhao, Kohei Hatano, Masashi Sugiyama