Lunjia Hu

Orcid: 0000-0003-1820-6800

According to our database1, Lunjia Hu authored at least 22 papers between 2017 and 2024.

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Bibliography

2024
Testing Calibration in Subquadratic Time.
CoRR, 2024

On Computationally Efficient Multi-Class Calibration.
CoRR, 2024

Loss Minimization Yields Multicalibration for Large Neural Networks.
Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

2023
A Unifying Theory of Distance from Calibration.
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Simple, Scalable and Effective Clustering via One-Dimensional Projections.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

When Does Optimizing a Proper Loss Yield Calibration?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes.
Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

Loss Minimization Through the Lens Of Outcome Indistinguishability.
Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

Omnipredictors for Constrained Optimization.
Proceedings of the International Conference on Machine Learning, 2023

Generative Models of Huge Objects.
Proceedings of the 38th Computational Complexity Conference, 2023

2022
An Improved Local Search Algorithm for k-Median.
Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

Near-Optimal Explainable k-Means for All Dimensions.
Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

Subspace Recovery from Heterogeneous Data with Non-isotropic Noise.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Approximation Algorithms for Orthogonal Non-negative Matrix Factorization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
The Power of Many Samples in Query Complexity.
Electron. Colloquium Comput. Complex., 2020

Robust and On-the-fly Dataset Denoising for Image Classification.
CoRR, 2020

2018
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Active Tolerant Testing.
Proceedings of the Conference On Learning Theory, 2018

2017
Capacitated Center Problems with Two-Sided Bounds and Outliers.
Proceedings of the Algorithms and Data Structures - 15th International Symposium, 2017

Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes.
Proceedings of the 30th Conference on Learning Theory, 2017


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