On Strategy-Proof Allocation without Payments or Priors. - Li Han; Chunzhi Su; Linpeng Tang; Hongyang Zhang 005 (WINE, 2011)

Computing the Nucleolus of Matching, Cover and Clique Games. - Ning Chen 005; Pinyan Lu; Hongyang Zhang 005 (AAAI, 2012)

Fixed-Parameter Tractability of almost CSP Problem with Decisive Relations. - Chihao Zhang 001; Hongyang Zhang 005 (FAW-AAIM, 2012)

Incentive Ratios of Fisher Markets. - Ning Chen 005; Xiaotie Deng; Hongyang Zhang 005; Jie Zhang 008 (ICALP (2), 2012)

Connectivity in Random Forests and Credit Networks. - Ashish Goel; Sanjeev Khanna; Sharath Raghvendra; Hongyang Zhang 005 (SODA, 2015)

A Note on Modeling Retweet Cascades on Twitter. - Ashish Goel; Kamesh Munagala; Aneesh Sharma; Hongyang Zhang 005 (WAW, 2015)

Incentives for Strategic Behavior in Fisher Market Games. - Ning Chen 005; Xiaotie Deng; Bo Tang 010; Hongyang Zhang 005 (AAAI, 2016)

Approximate Personalized PageRank on Dynamic Graphs. - Hongyang Zhang 005; Peter Lofgren; Ashish Goel (KDD, 2016)

Algorithmic Regularization in Over-parameterized Matrix Recovery. - Yuanzhi Li; Tengyu Ma 001; Hongyang Zhang 005 (CoRR, 2017)

Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations. - Yuanzhi Li; Tengyu Ma 001; Hongyang Zhang 005 (COLT, 2018)

Recovery Guarantees for Quadratic Tensors with Limited Observations. - Hongyang Zhang 005; Vatsal Sharan; Moses Charikar; Yingyu Liang (CoRR, 2018)

Recovery Guarantees For Quadratic Tensors With Sparse Observations. - Hongyang Zhang 005; Vatsal Sharan; Moses Charikar; Yingyu Liang (AISTATS, 2019)

Pruning based Distance Sketches with Provable Guarantees on Random Graphs. - Hongyang Zhang 005; Huacheng Yu; Ashish Goel (WWW, 2019)

Algorithms and generalization for large-scale matrices and tensors. - Hongyang R. Zhang (2019)

Learning Over-Parametrized Two-Layer Neural Networks beyond NTK. - Yuanzhi Li; Tengyu Ma 001; Hongyang R. Zhang (COLT, 2020)

Understanding and Improving Information Transfer in Multi-Task Learning. - Sen Wu 002; Hongyang R. Zhang; Christopher Ré (ICLR, 2020)

On the Generalization Effects of Linear Transformations in Data Augmentation. - Sen Wu 002; Hongyang R. Zhang; Gregory Valiant; Christopher Ré (ICML, 2020)

Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK. - Yuanzhi Li; Tengyu Ma 001; Hongyang R. Zhang (CoRR, 2020)

Sharp Bias-variance Tradeoffs of Hard Parameter Sharing in High-dimensional Linear Regression. - Hongyang R. Zhang; Fan Yang; Sen Wu 002; Weijie J. Su; Christopher Ré (CoRR, 2020)

Observational Supervision for Medical Image Classification Using Gaze Data. - Khaled Saab 002; Sarah M. Hooper; Nimit Sharad Sohoni; Jupinder Parmar; Brian Pogatchnik; Sen Wu 002; Jared A. Dunnmon; Hongyang R. Zhang; Daniel L. Rubin; Christopher Ré (MICCAI (2), 2021)

Improved Regularization and Robustness for Fine-tuning in Neural Networks. - Dongyue Li; Hongyang R. Zhang (NeurIPS, 2021)

Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees. - Haotian Ju; Dongyue Li; Hongyang R. Zhang (ICML, 2022)

Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations. - Michael Zhang; Nimit Sharad Sohoni; Hongyang R. Zhang; Chelsea Finn; Christopher Ré (ICML, 2022)

Improved Worst-Group Robustness via Classifier Retraining on Independent Splits. - Thien Hang Nguyen; Hongyang R. Zhang; Huy Le Nguyen (CoRR, 2022)

Incentive ratio: A game theoretical analysis of market equilibria. - Ning Chen 005; Xiaotie Deng; Bo Tang 010; Hongyang R. Zhang; Jie Zhang 008 (Inf. Comput., 2022)

Information Transfer in Multitask Learning, Data Augmentation, and Beyond. - Hongyang R. Zhang (AAAI, 2023)

Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion. - Haotian Ju; Dongyue Li; Aneesh Sharma; Hongyang R. Zhang (AISTATS, 2023)

Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. - Dongyue Li; Haotian Ju; Aneesh Sharma; Hongyang R. Zhang (KDD, 2023)

Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis. - Abhinav Nippani; Dongyue Li; Haotian Ju; Haris K. Koutsopoulos; Hongyang R. Zhang (NeurIPS, 2023)

Optimal Intervention on Weighted Networks via Edge Centrality. - Dongyue Li; Tina Eliassi-Rad; Hongyang R. Zhang (SDM, 2023)

Noise Stability Optimization for Flat Minima with Optimal Convergence Rates. - Haotian Ju; Dongyue Li; Hongyang R. Zhang (CoRR, 2023)

Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis. - Abhinav Nippani; Dongyue Li; Haotian Ju; Haris N. Koutsopoulos; Hongyang R. Zhang (CoRR, 2023)

Identification of Negative Transfers in Multitask Learning Using Surrogate Models. - Dongyue Li; Huy L. Nguyen; Hongyang Ryan Zhang (Trans. Mach. Learn. Res., 2023)

Improved Group Robustness via Classifier Retraining on Independent Splits. - Thien Hang Nguyen; Hongyang R. Zhang; Huy L. Nguyen (Trans. Mach. Learn. Res., 2023)

Scalable Fine-tuning from Multiple Data Sources: A First-Order Approximation Approach. - Dongyue Li; Ziniu Zhang; Lu Wang 008; Hongyang Zhang 005 (EMNLP (Findings), 2024)

Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity. - Dongyue Li; Aneesh Sharma; Hongyang R. Zhang (KDD, 2024)

Scalable Fine-tuning from Multiple Data Sources:A First-Order Approximation Approach. - Dongyue Li; Ziniu Zhang; Lu Wang 008; Hongyang R. Zhang (CoRR, 2024)

Learning Tree-Structured Composition of Data Augmentation. - Dongyue Li; Kailai Chen; Predrag Radivojac; Hongyang R. Zhang (Trans. Mach. Learn. Res., 2024)

Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach. - Hongyang R. Zhang; Dongyue Li; Haotian Ju (Trans. Mach. Learn. Res., 2024)

Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets. - Dongyue Li; Ziniu Zhang; Lu Wang 008; Hongyang R. Zhang (ACL (1), 2025)