See also DBLP for further bibliographic information.

Publications

• Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis, NeurIPS ’23 Data
  A. Nippani, D. Li, H. Ju, H. N. Koutsopoulos, and H. R. Zhang

• Improved Group Robustness via Classifier Retraining on Independent Splits, TMLR ’23
  T. H. Nguyen, H. R. Zhang, and H. L. Nguyen

• Boosting Multitask Learning on Graphs through Higher-Order Task Affinities, KDD ’23
  D. Li, H. Ju, A. Sharma, and H. R. Zhang

• Identification of Negative Transfers in Multitask Learning Using Surrogate Models, TMLR ’23. Featured Certification
  D. Li, H. L. Nguyen, and H. R. Zhang

• Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion, AISTATS ’23
  H. Ju, D. Li, A. Sharma, and H. R. Zhang

• Optimal Intervention on Weighted Networks via Edge Centrality, SDM ’23
  D. Li, T. Eliassi-Rad, and H. R. Zhang

• Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees, ICML ’22
  H. Ju, D. Li, and H. R. Zhang

• Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations, ICML ’22. Long presentation
  M. Zhang, N. Sohoni, H. R. Zhang, C. Finn, and C. Ré

• Incentive Ratio: A Game Theoretical Analysis of Market Equilibria, Information and Computation ’22
  N. Chen, X. Deng, B. Tang, H. R. Zhang, and J. Zhang

• Improved Regularization and Robustness for Fine-tuning in Neural Networks, NeurIPS ’21
  D. Li and H. R. Zhang

• Observational Supervision for Medical Image Classification using Gaze Data, MICCAI ’21
  K. Saab, S. Hooper, N. Sohoni, J. Dunnmon, H. R. Zhang, D. Rubin, and C. Ré

• On the Generalization Effects of Linear Transformations in Data Augmentation, ICML ’20
  S. Wu*, H. R. Zhang*, G. Valiant, and C. Ré

• Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK, COLT ’20
  Y. Li*, T. Ma*, and H. R. Zhang*

• Understanding and Improving Information Transfer in Multi-Task Learning, ICLR ’20
  S. Wu*, H. R. Zhang*, and C. Ré

• Algorithms and Generalization for Large-scale Matrices and Tensors, Ph.D. Thesis ’19, Stanford University
  H. Zhang

• Pruning based Distance Sketches with Provable Guarantees on Random Graphs, WWW ’19. Oral presentation
  H. Zhang, H. Yu, and A. Goel

• Recovery Guarantees for Quadratic Tensors with Sparse Observations, AISTATS ’19
  H. Zhang, V. Sharan, M. Charikar, and Y. Liang

• Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations, COLT ’18. Best Paper Award
  Y. Li*, T. Ma*, and H. Zhang*

• Approximate Personalized PageRank on Dynamic Graphs, KDD ’16. Oral presentation
  H. Zhang, P. Lofgren, and A. Goel

• Incentives for Strategic Behavior in Fisher Market Games, AAAI ’16
  N. Chen*, X. Deng*, B. Tang*, and H. Zhang*

• A Note on Modeling Retweet Cascades on Twitter, WAW ’15
  A. Goel*, K. Munagala*, A. Sharma*, and H. Zhang*

• Connectivity in Random Forests and Credit Networks, SODA ’15
  A. Goel*, S. Khanna*, S. Raghvendra*, and H. Zhang*

• Computing the Nucleolus of Matching, Cover and Clique Games, AAAI ’12. Oral presentation
  N. Chen*, P. Lu*, and H. Zhang*

• Incentive Ratios of Fisher Markets, ICALP ’12
  N. Chen*, X. Deng*, H. Zhang*, and J. Zhang*

• On Strategy-proof Allocation without Payments or Priors, WINE ’11
  L. Han*, C. Su*, L. Tang*, and H. Zhang*