Raghu Bollapragada
Raghu Bollapragada
Verified email at utexas.edu - Homepage
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Exact and inexact subsampled Newton methods for optimization
R Bollapragada, RH Byrd, J Nocedal
IMA Journal of Numerical Analysis 39 (2), 545-578, 2019
An investigation of Newton-sketch and subsampled Newton methods
AS Berahas, R Bollapragada, J Nocedal
Optimization Methods and Software, 1-20, 2020
A progressive batching L-BFGS method for machine learning
R Bollapragada, D Mudigere, J Nocedal, HJM Shi, PTP Tang
arXiv preprint arXiv:1802.05374, 2018
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
Adaptive sampling strategies for stochastic optimization
R Bollapragada, R Byrd, J Nocedal
SIAM Journal on Optimization 28 (4), 3312-3343, 2018
Nonlinear acceleration of momentum and primal-dual algorithms
R Bollapragada, D Scieur, A d'Aspremont
arXiv preprint arXiv:1810.04539, 2018
Nonlinear Acceleration of Primal-Dual Algorithms
R Bollapragada, D Scieur, A d’Aspremont
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Optimization and Machine Learning Training Algorithms for Fitting Numerical Physics Models
R Bollapragada, M Menickelly, W Nazarewicz, J O'Neal, PG Reinhard, ...
arXiv preprint arXiv:2010.05668, 2020
On the Convergence of Nested Decentralized Gradient Methods with Multiple Consensus and Gradient Steps
AS Berahas, R Bollapragada, E Wei
arXiv preprint arXiv:2006.01665, 2020
An Investigation of Newton-Sketch and Subsampled Newton Methods: Supplementary Materials
AS Berahas, R Bollapragada, J Nocedal
Adaptive Sampling Quasi-Newton Methods for Derivative-Free Stochastic Optimization
R Bollapragada, SM Wild
arXiv preprint arXiv:1910.13516, 2019
Kinematical Design of a Precision Cylindrical Grinder with Volumetric Error Modelling and Sensitivity Analysis
V Rajagopal, VR Bollapragada, RB Nimmagadda
International Journal of Precision Technology 6, 193-215, 2016
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