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ORCIDEnayat Ullah
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2020 – today
- 2024
[c12]Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán:
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. ALT 2024: 868-906- [i14]Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora
:
Public-data Assisted Private Stochastic Optimization: Power and Limitations. CoRR abs/2403.03856 (2024) - 2023
- [j2]Enayat Ullah, Raman Arora:
Generalization bounds for Kernel Canonical Correlation Analysis. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Enayat Ullah, Harry Lang, Raman Arora, Vladimir Braverman:
Clustering using Approximate Nearest Neighbour Oracles. Trans. Mach. Learn. Res. 2023 (2023) - [c11]Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. ICML 2023: 1060-1092 - [c10]Enayat Ullah, Raman Arora:
From Adaptive Query Release to Machine Unlearning. ICML 2023: 34642-34667 - [c9]Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh:
Private Federated Learning with Autotuned Compression. ICML 2023: 34668-34708 - [c8]Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora:
Optimistic Rates for Multi-Task Representation Learning. NeurIPS 2023 - [i13]Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh:
Private Federated Learning with Autotuned Compression. CoRR abs/2307.10999 (2023) - [i12]Enayat Ullah, Raman Arora:
From Adaptive Query Release to Machine Unlearning. CoRR abs/2307.11228 (2023) - [i11]Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán:
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. CoRR abs/2311.13447 (2023) - 2022
- [c7]Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Differentially Private Generalized Linear Models Revisited. NeurIPS 2022 - [c6]Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora:
Adversarial Robustness is at Odds with Lazy Training. NeurIPS 2022 - [i10]Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Differentially Private Generalized Linear Models Revisited. CoRR abs/2205.03014 (2022) - [i9]Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. CoRR abs/2206.00846 (2022) - [i8]Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora:
Adversarial Robustness is at Odds with Lazy Training. CoRR abs/2207.00411 (2022) - 2021
- [c5]Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora:
Machine Unlearning via Algorithmic Stability. COLT 2021: 4126-4142 - [i7]Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora:
Machine Unlearning via Algorithmic Stability. CoRR abs/2102.13179 (2021) - 2020
- [c4]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. ICML 2020: 8253-8265 - [i6]Raman Arora, Teodor V. Marinov, Enayat Ullah:
Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives. CoRR abs/2002.09609 (2020) - [i5]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. CoRR abs/2007.07682 (2020)
2010 – 2019
- 2019
- [c3]Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou:
Improved Algorithms for Time Decay Streams. APPROX-RANDOM 2019: 27:1-27:17 - [c2]Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora:
Communication-efficient Distributed SGD with Sketching. NeurIPS 2019: 13144-13154 - [i4]Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora:
Communication-efficient distributed SGD with Sketching. CoRR abs/1903.04488 (2019) - [i3]Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou:
Improved Algorithms for Time Decay Streams. CoRR abs/1907.07574 (2019) - 2018
- [c1]Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora:
Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features. NeurIPS 2018: 7322-7332 - [i2]Amitabh Basu, Soham De, Anirbit Mukherjee, Enayat Ullah:
Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders. CoRR abs/1807.06766 (2018) - [i1]Enayat Ullah, Poorya Mianjy, Teodor V. Marinov, Raman Arora:
Streaming Kernel PCA with Õ(√n) Random Features. CoRR abs/1808.00934 (2018)
Coauthor Index
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