Naman Agarwal
Naman Agarwal
Senior Research Scientist, Google AI Princeton
Verified email at - Homepage
Cited by
Cited by
cpSGD: Communication-efficient and differentially-private distributed SGD
N Agarwal, AT Suresh, F Yu, S Kumar, HB Mcmahan
(Spotlight) 32nd International Conference on Neural Information Processing …, 2018
Finding Approximate Local Minima for Nonconvex Optimization in Linear Time
N Agarwal, AZ Zeyuan, B Brian, E Hazan, T Ma
Symposium on Theory of Computing 2017, 2016
Second-order stochastic optimization for machine learning in linear time
N Agarwal, B Bullins, E Hazan
Journal of Machine Learning Research 18 (116), 1-40, 2017
Online control with adversarial disturbances
N Agarwal, B Bullins, E Hazan, S Kakade, K Singh
International Conference on Machine Learning, 111-119, 2019
The skellam mechanism for differentially private federated learning
N Agarwal, P Kairouz, Z Liu
Advances in Neural Information Processing Systems 34, 5052-5064, 2021
Logarithmic regret for online control
N Agarwal, E Hazan, K Singh
(Oral) Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2019
The price of differential privacy for online learning
N Agarwal, K Singh
International Conference on Machine Learning, 32-40, 2017
The case for full-matrix adaptive regularization
N Agarwal, B Bullins, X Chen, E Hazan, K Singh, C Zhang, Y Zhang
International Conference on Machine Learning, 2019, 2018
Adaptive regularization with cubics on manifolds
N Agarwal, N Boumal, B Bullins, C Cartis
Mathematical Programming 188, 85-134, 2021
Multisection in the stochastic block model using semidefinite programming
N Agarwal, AS Bandeira, K Koiliaris, A Kolla
Compressed Sensing and its Applications: Second MATHEON Conference 2015, 2015
Learning in non-convex games with an optimization oracle
N Agarwal, A Gonen, E Hazan
Conference on Learning Theory, 18-29, 2019
Lower bounds for higher-order convex optimization
N Agarwal, E Hazan
Conference On Learning Theory, 774-792, 2018
Adaptive gradient methods at the edge of stability
JM Cohen, B Ghorbani, S Krishnan, N Agarwal, S Medapati, M Badura, ...
arXiv preprint arXiv:2207.14484, 2022
Disentangling adaptive gradient methods from learning rates
N Agarwal, R Anil, E Hazan, T Koren, C Zhang
arXiv preprint arXiv:2002.11803, 2020
Online target q-learning with reverse experience replay: Efficiently finding the optimal policy for linear mdps
N Agarwal, S Chaudhuri, P Jain, D Nagaraj, P Netrapalli
arXiv preprint arXiv:2110.08440, 2021
Leverage score sampling for faster accelerated regression and ERM
N Agarwal, S Kakade, R Kidambi, YT Lee, P Netrapalli, A Sidford
Algorithmic Learning Theory, 22-47, 2020
Acceleration via fractal learning rate schedules
N Agarwal, S Goel, C Zhang
International Conference on Machine Learning, 87-99, 2021
A regret minimization approach to iterative learning control
N Agarwal, E Hazan, A Majumdar, K Singh
International Conference on Machine Learning, 100-109, 2021
On the expansion of group-based lifts
N Agarwal, K Chandrasekaran, A Kolla, V Madan
SIAM Journal on Discrete Mathematics 33 (3), 1338-1373, 2019
Pushing the efficiency-regret pareto frontier for online learning of portfolios and quantum states
J Zimmert, N Agarwal, S Kale
Conference on Learning Theory, 182-226, 2022
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