Gautam Kamath
Orcid: 0000-0003-0048-2559Affiliations:
- University of Waterloo, Cheriton School of Computer Science, ON, Canada
- University of California, Berkeley, Simons Institute for the Theory of Computing, CA, USA
- Massachusetts Institute of Technology (MIT), CSAIL, Cambridge, MA, USA (PhD 2018)
- Microsoft Research New England, Cambridge, MA, USA
- Cornell University, Department of Computer Science, Ithaca, NY, USA
According to our database1,
Gautam Kamath
authored at least 65 papers
between 2012 and 2024.
Collaborative distances:
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Bibliography
2024
2023
Choosing Public Datasets for Private Machine Learning via Gradient Subspace Distance.
CoRR, 2023
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
Trans. Mach. Learn. Res., 2022
Introduction to the Special Issue on ACM-SIAM Symposium on Discrete Algorithms (SODA) 2020.
ACM Trans. Algorithms, 2022
Considerations for Differentially Private Learning with Large-Scale Public Pretraining.
CoRR, 2022
Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent.
CoRR, 2022
Efficient mean estimation with pure differential privacy via a sum-of-squares exponential mechanism.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the IEEE International Symposium on Information Theory, 2022
Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy.
CoRR, 2021
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the Algorithmic Learning Theory, 2021
2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Conference on Learning Theory, 2020
Proceedings of the Conference on Learning Theory, 2020
2019
SIAM J. Comput., 2019
Random Restrictions of High-Dimensional Distributions and Uniformity Testing with Subcube Conditioning.
Electron. Colloquium Comput. Complex., 2019
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Conference on Learning Theory, 2019
2018
Theory Comput., 2018
Electron. Colloquium Comput. Complex., 2018
Electron. Colloquium Comput. Complex., 2018
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018
Proceedings of the Conference On Learning Theory, 2018
2017
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
A Framework for Testing Properties of Discrete Distributions: Monotonicity, Independence, and More.
Tiny Trans. Comput. Sci., 2016
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the IEEE International Symposium on Information Theory, 2015
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015
2014
Proceedings of The 27th Conference on Learning Theory, 2014
2012
Proceedings of the 44th Symposium on Theory of Computing Conference, 2012