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2020 – today
- 2024
[j9]Albert S. Berahas, Raghu Bollapragada, Shagun Gupta:
Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization. J. Optim. Theory Appl. 203(3): 2954-2987 (2024)- [j8]Suhail M. Shah
, Albert S. Berahas, Raghu Bollapragada:
Adaptive Consensus: A Network Pruning Approach for Decentralized Optimization. SIAM J. Optim. 34(4): 3653-3680 (2024) - [i5]Thomas O'Leary-Roseberry, Raghu Bollapragada:
Fast Unconstrained Optimization via Hessian Averaging and Adaptive Gradient Sampling Methods. CoRR abs/2408.07268 (2024) - 2023
- [j7]Raghu Bollapragada, Cem Karamanli, Brendan Keith, Boyan Lazarov, Socratis Petrides, Jingyi Wang:
An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints. Comput. Math. Appl. 149: 239-258 (2023) - [j6]Raghu Bollapragada, Damien Scieur, Alexandre d'Aspremont:
Nonlinear acceleration of momentum and primal-dual algorithms. Math. Program. 198(1): 325-362 (2023) - [j5]Raghu Bollapragada, Stefan M. Wild:
Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization. Math. Program. Comput. 15(2): 327-364 (2023) - 2022
- [c3]Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, Matthew Lease:
Learning a neural Pareto manifold extractor with constraints. UAI 2022: 749-758 - [i4]Raghu Bollapragada, Tyler Chen, Rachel A. Ward:
On the fast convergence of minibatch heavy ball momentum. CoRR abs/2206.07553 (2022) - 2021
- [j4]Albert S. Berahas, Raghu Bollapragada, Ermin Wei:
On the Convergence of Nested Decentralized Gradient Methods With Multiple Consensus and Gradient Steps. IEEE Trans. Signal Process. 69: 4192-4203 (2021) - [i3]Raghu Bollapragada, Stefan M. Wild:
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization. CoRR abs/2109.12213 (2021) - 2020
- [j3]Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal:
An investigation of Newton-Sketch and subsampled Newton methods. Optim. Methods Softw. 35(4): 661-680 (2020)
2010 – 2019
- 2019
- [j2]Albert S. Berahas, Raghu Bollapragada, Nitish Shirish Keskar, Ermin Wei:
Balancing Communication and Computation in Distributed Optimization. IEEE Trans. Autom. Control. 64(8): 3141-3155 (2019) - [c2]Raghu Bollapragada, Damien Scieur, Alexandre d'Aspremont:
Nonlinear Acceleration of Primal-Dual Algorithms. AISTATS 2019: 739-747 - 2018
- [j1]Raghu Bollapragada, Richard H. Byrd, Jorge Nocedal:
Adaptive Sampling Strategies for Stochastic Optimization. SIAM J. Optim. 28(4): 3312-3343 (2018) - [c1]Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang:
A Progressive Batching L-BFGS Method for Machine Learning. ICML 2018: 619-628 - [i2]Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang:
A Progressive Batching L-BFGS Method for Machine Learning. CoRR abs/1802.05374 (2018) - 2017
- [i1]Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal:
An Investigation of Newton-Sketch and Subsampled Newton Methods. CoRR abs/1705.06211 (2017)
Coauthor Index
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