Gavin Brown

According to our database, Gavin Brown authored at least 12 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares.

Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith

CoRR, 2024

Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation.

Gavin Brown, Krishnamurthy Dj Dvijotham, Georgina Evans, Daogao Liu, Adam Smith, Abhradeep Guha Thakurta

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Metalearning with Very Few Samples Per Task.

Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Nathan Srebro, Jonathan R. Ullman

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract.

Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Metalearning with Very Few Samples Per Task.

Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Jonathan R. Ullman

CoRR, 2023

Fast, Sample-Efficient, Affine-Invariant Private Mean and Covariance Estimation for Subgaussian Distributions.

Gavin Brown, Samuel B. Hopkins, Adam D. Smith

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Strong Memory Lower Bounds for Learning Natural Models.

Gavin Brown, Mark Bun, Adam D. Smith

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Performative Prediction in a Stateful World.

Gavin Brown, Shlomi Hod, Iden Kalemaj

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

When is memorization of irrelevant training data necessary for high-accuracy learning?

Gavin Brown, Mark Bun, Vitaly Feldman, Adam D. Smith, Kunal Talwar

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Covariance-Aware Private Mean Estimation Without Private Covariance Estimation.

Gavin Brown, Marco Gaboardi, Adam D. Smith, Jonathan R. Ullman, Lydia Zakynthinou

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Mixed Spatio-Temporal Neural Networks on Real-time Prediction of Crimes.

Xiao Zhou, Xiao Wang, Gavin Brown, Chengchen Wang, Peter Chin

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2017

A Mathematical Analysis of Network Controllability Through Driver Nodes.

Sang Peter Chin, Jonathan Cohen, Alison Albin, Mykola Hayvanovych, Elizabeth Reilly, Gavin Brown, Jacob Harer

IEEE Trans. Comput. Soc. Syst., 2017