Hu, Lunjia

14 publications

NeurIPS 2025 How Many Domains Suffice for Domain Generalization? a Tight Characterization via the Domain Shattering Dimension Cynthia Dwork, Lunjia Hu, Han Shao

ICML 2024 Multigroup Robustness Lunjia Hu, Charlotte Peale, Judy Hanwen Shen

COLT 2024 On Computationally Efficient Multi-Class Calibration Parikshit Gopalan, Lunjia Hu, Guy N. Rothblum

NeurIPS 2024 Testing Calibration in Nearly-Linear Time Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang

ICML 2023 Omnipredictors for Constrained Optimization Lunjia Hu, Inbal Rachel Livni Navon, Omer Reingold, Chutong Yang

NeurIPS 2023 Simple, Scalable and Effective Clustering via One-Dimensional Projections Moses Charikar, Monika Henzinger, Lunjia Hu, Maximilian Vötsch, Erik Waingarten

NeurIPS 2023 When Does Optimizing a Proper Loss Yield Calibration? Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran

ALT 2022 Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability Lunjia Hu, Charlotte Peale, Omer Reingold

NeurIPS 2022 Subspace Recovery from Heterogeneous Data with Non-Isotropic Noise John C. Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar

AISTATS 2021 Approximation Algorithms for Orthogonal Non-Negative Matrix Factorization Moses Charikar, Lunjia Hu

AISTATS 2021 Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers Lunjia Hu, Omer Reingold

COLT 2018 Active Tolerant Testing Avrim Blum, Lunjia Hu

NeurIPS 2018 Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation Liwei Wang, Lunjia Hu, Jiayuan Gu, Zhiqiang Hu, Yue Wu, Kun He, John Hopcroft

COLT 2017 Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes Lunjia Hu, Ruihan Wu, Tianhong Li, Liwei Wang