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Scalable Fine-tuning From Multiple Data Sources: A First-Order Approximation Approach
Dongyue Li*, Ziniu Zhang*, Lu Wang, Hongyang R. Zhang
Findings of EMNLP 2024
[Code]
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Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach
Hongyang R. Zhang, Dongyue Li, Haotian Ju
TMLR 2024
[Code]
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Learning Tree-Structured Composition of Data Augmentation
Dongyue Li, Kailai Chen, Predrag Radivojac, Hongyang R. Zhang
TMLR 2024
[Code]
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Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity
Dongyue Li, Aneesh Sharma, Hongyang R. Zhang
KDD 2024
[Code][Video]
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Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang
KDD 2023
[Code]
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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
NeurIPS 2023, Datasets and Benchmarks Track
[ML4RoadSafety Package]
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Identification of Negative Transfers in Multitask Learning Using Surrogate Models
Dongyue Li, Huy L. Nguyen, Hongyang R. Zhang
TMLR 2023 (Featured Certification)
[Code] [Presented in NeurIPS Workshop on Distribution Shifts 2022]
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Optimal Intervention on Weighted Networks via Edge Centrality
Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang
SDM 2023
[Code] [Presented in KDD epiDAMIK Workshop 2022]
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Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju, Dongyue Li, Aneesh Sharma, Hongyang R. Zhang
AISTATS 2023
[Code]
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Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees
Haotian Ju*, Dongyue Li*, Hongyang R. Zhang
ICML 2022
[Code] [Presented in ICML UpML Workshop 2022]
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Improved Regularization and Robustness for Fine-tuning in Neural Networks
Dongyue Li, Hongyang R. Zhang
NeurIPS 2021
[Code]
Prior to my Ph.D. study
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DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture
Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He and Li Jiang
DATE 2022
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AdaptiveGCN: Efficient GCN Through Adaptively Sparsifying Graphs
Dongyue Li*, Tao Yang*, Lun Du, Zhezhi He, and Li Jiang
CIKM 2021, Short paper.
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PIMGCN: A ReRAM-based PIM Design for Graph Convolutional Network Acceleration
Tao Yang, Dongyue Li, Yibo Han, Yilong Zhao, Fangxin Liu, Xiaoyao Liang, Zhezhi He, and Li Jiang
DAC 2021
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ReRAM-Sharing: Fine-Grained Weight Sharing for ReRAM-Based Deep Neural Network Accelerator
Dongyue Li*, Zhuoran Song*, Zhezhi He, Xiaoyao Liang, and Li Jiang
ISCAS 2021
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Personalized and Environment-Aware Battery Prediction for Electric Vehicles
Dongyue Li*, Guangyu Li*, Bo Jiang*, Zhengping Che, and Yan Liu
KDD MiLeTS Workshop 2021
Asterisk(*) indicates equal contribution
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Applied Research Intern
Capital One, New York, Jun. 2024 to Aug. 2024
Mentors: Nam Nguyen, Gang Mei, Sam Sharpe, Senthil Kumar, and Bayan Bruss
Predoctoral Researcher
Shanghai Qi Zhi Institute, Shanghai, Aug. 2020 to May. 2021
Mentors: Li Jiang
Research Intern
DiDi Chuxing AI Labs, Beijing, Jul. 2019 to Sep. 2019
Mentors: Yan Liu
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