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Manuscripts
One-Sided Matrix Completion from Ultra-Sparse Samples. H. R. Zhang, Z. Zhang, H. L. Nguyen, and G. Lan.
2025
Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation. Z. Zhang*, Z. Zhang*, D. Li, L. Wang, J. Dy, and H. R. Zhang. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers. F. Yang*, H. R. Zhang*, S. Wu, C. Ré, and W. Su. Journal of Machine Learning Research (JMLR), 2025
Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets. D. Li, Z. Zhang, L. Wang, and H. R. Zhang. Association for Computational Linguistics (ACL), 2025
2024
Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach. H. R. Zhang, D. Li, and H. Ju. Transactions on Machine Learning Research (TMLR), 2024
Scalable Fine-tuning From Multiple Data Sources: A First-order Approximation Approach. D. Li, Z. Zhang, L. Wang, and H. R. Zhang. Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP), 2024
Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity. D. Li, A. Sharma, and H. R. Zhang. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2024
Learning Tree-Structured Composition of Data Augmentation. D. Li, K. Chen, P. Radivojac, and H. R. Zhang. Transactions on Machine Learning Research (TMLR), 2024
2023
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis. A. Nippani, D. Li, H. Ju, H. N. Koutsopoulos, and H. R. Zhang. Neural Information Processing Systems (NeurIPS Datasets Track), 2023
Improved Group Robustness via Classifier Retraining on Independent Splits. T. H. Nguyen, H. R. Zhang, and H. L. Nguyen. Transactions on Machine Learning Research (TMLR), 2023
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. D. Li, H. Ju, A. Sharma, and H. R. Zhang. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
Identification of Negative Transfers in Multitask Learning Using Surrogate Models. D. Li, H. L. Nguyen, and H. R. Zhang. Transactions on Machine Learning Research (TMLR), 2023. Featured Certification
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion. H. Ju, D. Li, A. Sharma, and H. R. Zhang. Artificial Intelligence and Statistics (AISTATS), 2023
Optimal Intervention on Weighted Networks via Edge Centrality. D. Li, T. Eliassi-Rad, and H. R. Zhang. SIAM International Conference on Data Mining (SDM), 2023
2022
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees. H. Ju, D. Li, and H. R. Zhang. International Conference on Machine Learning (ICML), 2022
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations. M. Zhang, N. Sohoni, H. R. Zhang, C. Finn, and C. Ré. International Conference on Machine Learning (ICML), 2022. Long presentation
Incentive Ratio: A Game Theoretical Analysis of Market Equilibria. N. Chen, X. Deng, B. Tang, H. R. Zhang, and J. Zhang. Information and Computation, 2022
2021
Improved Regularization and Robustness for Fine-tuning in Neural Networks. D. Li and H. R. Zhang. Neural Information Processing Systems (NeurIPS), 2021
Observational Supervision for Medical Image Classification using Gaze Data. K. Saab, S. Hooper, N. Sohoni, J. Parmar, B. Pogatchnik, S. Wu, J. Dunnmon, H. R. Zhang, D. Rubin, and C. Ré. Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021
2020
On the Generalization Effects of Linear Transformations in Data Augmentation. S. Wu*, H. R. Zhang*, G. Valiant, and C. Ré. International Conference on Machine Learning (ICML), 2020
Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK. Y. Li*, T. Ma*, and H. R. Zhang*. Annual Conference on Learning Theory (COLT), 2020
Understanding and Improving Information Transfer in Multi-Task Learning. S. Wu*, H. R. Zhang*, and C. Ré. International Conference on Learning Representations (ICLR), 2020
Prior to 2019
Algorithms and Generalization for Large-scale Matrices and Tensors. Thesis Ph.D. Stanford University, 2019
Pruning based Distance Sketches with Provable Guarantees on Random Graphs. H. Zhang, H. Yu, and A. Goel. The Web Conference (WWW) 2019. Oral presentation. [code]
Recovery Guarantees for Quadratic Tensors with Sparse Observations. H. Zhang, V. Sharan, M. Charikar, and Y. Liang. Artificial Intelligence and Statistics (AISTATS), 2019
Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations. Y. Li*, T. Ma*, and H. Zhang*. Conference on Learning Theory (COLT) 2018. Best Paper Award
Approximate Personalized PageRank on Dynamic Graphs. H. Zhang, P. Lofgren, and A. Goel. KDD 2016. Oral presentation. [code]
Incentives for Strategic Behavior in Fisher Market Games. N. Chen*, X. Deng*, B. Tang*, and H. Zhang*. AAAI, 2016
A Note on Modeling Retweet Cascades on Twitter. A. Goel*, K. Munagala*, A. Sharma*, and H. Zhang*. Workshop on Algorithms and Models for the Web Graph (WAW), 2015
Connectivity in Random Forests and Credit Networks. A. Goel*, S. Khanna*, S. Raghvendra*, and H. Zhang*. Symposium on Discrete Algorithms (SODA), 2015
Computing the Nucleolus of Matching, Cover and Clique Games. N. Chen*, P. Lu*, and H. Zhang*. AAAI, 2012. Oral presentation
Incentive Ratios of Fisher Markets. N. Chen*, X. Deng*, H. Zhang*, and J. Zhang*. International Colloquium on Automata, Languages, and Programming (ICALP), 2012
Fixed-Parameter Tractability of almost CSP Problem with Decisive Relations. C. Zhang and H. Zhang. FAW-AAIM, 2012
On Strategy-proof Allocation without Payments or Priors. L. Han*, C. Su*, L. Tang*, and H. Zhang*. Conference on Web and Internet Economics (WINE), 2011
Remark: The papers above that are marked by stars follow the convention of alphabetical ordering of author names.