Hongyang R. Zhang

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 30

Top Topics

Multitask Learning

Theoretical Analysis

Top Venues

Trans. Mach. Learn. Res.

Publications

Dongyue Li, Aneesh Sharma, Hongyang R. Zhang
Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity. KDD (2024)
Dongyue Li, Kailai Chen, Predrag Radivojac, Hongyang R. Zhang
Learning Tree-Structured Composition of Data Augmentation. Trans. Mach. Learn. Res. 2024 (2024)
Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. KDD (2023)
Haotian Ju, Dongyue Li, Hongyang R. Zhang
Noise Stability Optimization for Flat Minima with Optimal Convergence Rates. CoRR (2023)
Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang
Optimal Intervention on Weighted Networks via Edge Centrality. CoRR (2023)
Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. CoRR (2023)
Thien Hang Nguyen, Hongyang R. Zhang, Huy L. Nguyen
Improved Group Robustness via Classifier Retraining on Independent Splits. Trans. Mach. Learn. Res. 2023 (2023)
Hongyang R. Zhang
Information Transfer in Multitask Learning, Data Augmentation, and Beyond. AAAI (2023)
Abhinav Nippani, Dongyue Li, Haotian Ju, Haris K. Koutsopoulos, Hongyang R. Zhang
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis. NeurIPS (2023)
Haotian Ju, Dongyue Li, Aneesh Sharma, Hongyang R. Zhang
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion. CoRR (2023)
Dongyue Li, Huy L. Nguyen, Hongyang R. Zhang
Identification of Negative Transfers in Multitask Learning Using Surrogate Models. CoRR (2023)
Haotian Ju, Dongyue Li, Aneesh Sharma, Hongyang R. Zhang
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion. AISTATS (2023)
Abhinav Nippani, Dongyue Li, Haotian Ju, Haris N. Koutsopoulos, Hongyang R. Zhang
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis. CoRR (2023)
Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang
Optimal Intervention on Weighted Networks via Edge Centrality. SDM (2023)
Michael Zhang, Nimit Sharad Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher Ré
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations. CoRR (2022)
Thien Hang Nguyen, Hongyang R. Zhang, Huy Le Nguyen
Improved Worst-Group Robustness via Classifier Retraining on Independent Splits. CoRR (2022)
Haotian Ju, Dongyue Li, Hongyang R. Zhang
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees. CoRR (2022)
Ning Chen, Xiaotie Deng, Bo Tang, Hongyang R. Zhang, Jie Zhang
Incentive ratio: A game theoretical analysis of market equilibria. Inf. Comput. 285 (Part) (2022)
Michael Zhang, Nimit Sharad Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher Ré
Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations. ICML (2022)
Haotian Ju, Dongyue Li, Hongyang R. Zhang
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees. ICML (2022)
Khaled Saab, Sarah M. Hooper, Nimit Sharad Sohoni, Jupinder Parmar, Brian Pogatchnik, Sen Wu, Jared A. Dunnmon, Hongyang R. Zhang, Daniel L. Rubin, Christopher Ré
Observational Supervision for Medical Image Classification Using Gaze Data. MICCAI (2) (2021)
Dongyue Li, Hongyang R. Zhang
Improved Regularization and Robustness for Fine-tuning in Neural Networks. CoRR (2021)
Dongyue Li, Hongyang R. Zhang
Improved Regularization and Robustness for Fine-tuning in Neural Networks. NeurIPS (2021)
Yuanzhi Li, Tengyu Ma, Hongyang R. Zhang
Learning Over-Parametrized Two-Layer Neural Networks beyond NTK. COLT (2020)
Yuanzhi Li, Tengyu Ma, Hongyang R. Zhang
Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK. CoRR (2020)
Sen Wu, Hongyang R. Zhang, Christopher Ré
Understanding and Improving Information Transfer in Multi-Task Learning. CoRR (2020)
Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher Ré
On the Generalization Effects of Linear Transformations in Data Augmentation. CoRR (2020)
Hongyang R. Zhang, Fan Yang, Sen Wu, Weijie J. Su, Christopher Ré
Sharp Bias-variance Tradeoffs of Hard Parameter Sharing in High-dimensional Linear Regression. CoRR (2020)
Sen Wu, Hongyang R. Zhang, Christopher Ré
Understanding and Improving Information Transfer in Multi-Task Learning. ICLR (2020)
Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher Ré
On the Generalization Effects of Linear Transformations in Data Augmentation. ICML (2020)