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Raghu Bollapragada
Raghu Bollapragada
Verified email at utexas.edu - Homepage
Title
Cited by
Cited by
Year
Exact and inexact subsampled Newton methods for optimization
R Bollapragada, RH Byrd, J Nocedal
IMA Journal of Numerical Analysis 39 (2), 545-578, 2019
1932019
A progressive batching L-BFGS method for machine learning
R Bollapragada, J Nocedal, D Mudigere, HJ Shi, PTP Tang
International Conference on Machine Learning, 620-629, 2018
1662018
Adaptive sampling strategies for stochastic optimization
R Bollapragada, R Byrd, J Nocedal
SIAM Journal on Optimization 28 (4), 3312-3343, 2018
1302018
An investigation of Newton-sketch and subsampled Newton methods
AS Berahas, R Bollapragada, J Nocedal
Optimization Methods and Software 35 (4), 661-680, 2020
1212020
Balancing communication and computation in distributed optimization
AS Berahas, R Bollapragada, NS Keskar, E Wei
IEEE Transactions on Automatic Control 64 (8), 3141-3155, 2018
1182018
Nonlinear acceleration of momentum and primal-dual algorithms
R Bollapragada, D Scieur, A d'Aspremont
arXiv preprint arXiv:1810.04539, 2018
31*2018
On the fast convergence of minibatch heavy ball momentum
R Bollapragada, T Chen, R Ward
arXiv preprint arXiv:2206.07553, 2022
222022
Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization
R Bollapragada, SM Wild
Mathematical Programming Computation 15 (2), 327-364, 2023
17*2023
On the convergence of nested decentralized gradient methods with multiple consensus and gradient steps
AS Berahas, R Bollapragada, E Wei
IEEE Transactions on Signal Processing 69, 4192-4203, 2021
172021
Optimization and supervised machine learning methods for fitting numerical physics models without derivatives
R Bollapragada, M Menickelly, W Nazarewicz, J O’Neal, PG Reinhard, ...
Journal of Physics G: Nuclear and Particle Physics 48 (2), 024001, 2020
152020
Constrained and composite optimization via adaptive sampling methods
Y Xie, R Bollapragada, R Byrd, J Nocedal
IMA Journal of Numerical Analysis 44 (2), 680-709, 2024
92024
An adaptive sampling sequential quadratic programming method for equality constrained stochastic optimization
AS Berahas, R Bollapragada, B Zhou
arXiv preprint arXiv:2206.00712, 2022
82022
Nonlinear acceleration of primal-dual algorithms
R Bollapragada, D Scieur, A d’Aspremont
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
72019
Scalable unidirectional Pareto optimality for multi-task learning with constraints
S Gupta, G Singh, R Bollapragada, M Lease
arXiv preprint arXiv:2110.15442, 2021
62021
An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints
R Bollapragada, C Karamanli, B Keith, B Lazarov, S Petrides, J Wang
Computers & Mathematics with Applications 149, 239-258, 2023
42023
Balancing communication and computation in gradient tracking algorithms for decentralized optimization
AS Berahas, R Bollapragada, S Gupta
arXiv preprint arXiv:2303.14289, 2023
42023
Adaptive Consensus: A network pruning approach for decentralized optimization
SM Shah, AS Berahas, R Bollapragada
arXiv preprint arXiv:2309.02626, 2023
12023
A stochastic gradient tracking algorithm for decentralized optimization with inexact communication
SM Shah, R Bollapragada
arXiv preprint arXiv:2307.14942, 2023
12023
Retrospective approximation for smooth stochastic optimization
D Newton
Purdue University, 2023
12023
Modified Line Search Sequential Quadratic Methods for Equality-Constrained Optimization with Unified Global and Local Convergence Guarantees
AS Berahas, R Bollapragada, J Shi
arXiv preprint arXiv:2406.11144, 2024
2024
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