Enayat Ullah

According to our database, Enayat Ullah authored at least 18 papers between 2018 and 2024.

Collaborative distances:

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

2024

Public-data Assisted Private Stochastic Optimization: Power and Limitations.

Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora

CoRR, 2024

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates.

Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Clustering using Approximate Nearest Neighbour Oracles.

Enayat Ullah, Harry Lang, Raman Arora, Vladimir Braverman

Trans. Mach. Learn. Res., 2023

Generalization bounds for Kernel Canonical Correlation Analysis.

Enayat Ullah, Raman Arora

Trans. Mach. Learn. Res., 2023

Optimistic Rates for Multi-Task Representation Learning.

Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Private Federated Learning with Autotuned Compression.

Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh

Proceedings of the International Conference on Machine Learning, 2023

From Adaptive Query Release to Machine Unlearning.

Enayat Ullah, Raman Arora

Proceedings of the International Conference on Machine Learning, 2023

Faster Rates of Convergence to Stationary Points in Differentially Private Optimization.

Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah

Proceedings of the International Conference on Machine Learning, 2023

2022

Adversarial Robustness is at Odds with Lazy Training.

Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differentially Private Generalized Linear Models Revisited.

Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Machine Unlearning via Algorithmic Stability.

Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora

Proceedings of the Conference on Learning Theory, 2021

2020

Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives.

Raman Arora, Teodor V. Marinov, Enayat Ullah

CoRR, 2020

FetchSGD: Communication-Efficient Federated Learning with Sketching.

Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Communication-efficient Distributed SGD with Sketching.

Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Improved Algorithms for Time Decay Streams.

Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou

Proceedings of the Approximation, 2019

2018

Streaming Kernel PCA with Õ(√n) Random Features.

Enayat Ullah, Poorya Mianjy, Teodor V. Marinov, Raman Arora

CoRR, 2018

Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders.

Amitabh Basu, Soham De, Anirbit Mukherjee, Enayat Ullah

CoRR, 2018

Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features.

Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018