Aryan Mokhtari
Aryan Mokhtari
Assistant Professor, ECE, University of Texas at Austin
Verified email at austin.utexas.edu - Homepage
Title
Cited by
Cited by
Year
RES: Regularized Stochastic BFGS Algorithm
A Mokhtari, A Ribeiro
IEEE Transactions on Signal Processing 62 (23), 6089-6104, 2014
1182014
Global Convergence of Online Limited Memory BFGS
A Mokhtari, A Ribeiro
Journal of Machine Learning Research 16, 3151-3181, 2015
1092015
DSA: Decentralized double stochastic averaging gradient algorithm
A Mokhtari, A Ribeiro
The Journal of Machine Learning Research 17 (1), 2165-2199, 2016
992016
Network Newton distributed optimization methods
A Mokhtari, Q Ling, A Ribeiro
IEEE Transactions on Signal Processing 65 (1), 146-161, 2017
882017
DQM: Decentralized Quadratically Approximated Alternating Direction Method of Multipliers
A Mokhtari, W Shi, Q Ling, A Ribeiro
IEEE Transactions on Signal Processing 64 (19), 5158-5173, 2016
812016
Online Optimization in Dynamic Environments: Improved Regret Rates for Strongly Convex Problems
A Mokhtari, S Shahrampour, A Jadbabaie, A Ribeiro
Decision and Control (CDC), 2016 IEEE 55th Conference on, 7195-7201, 2016
782016
A Decentralized Second-Order Method with Exact Linear Convergence Rate for Consensus Optimization
A Mokhtari, W Shi, Q Ling, A Ribeiro
IEEE Transactions on Signal and Information Processing over Networks 2 (4 …, 2016
692016
A Class of Prediction-Correction Methods for Time-Varying Convex Optimization
A Simonetto, A Mokhtari, A Koppel, G Leus, A Ribeiro
IEEE Transactions on Signal Processing 64 (17), 4576-4591, 2016
672016
Decentralized Quasi-Newton Methods
M Eisen, A Mokhtari, A Ribeiro
IEEE Transactions on Signal Processing 65 (10), 2613 - 2628, 2017
592017
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
A Mokhtari, A Ozdaglar, S Pattathil
International Conference on Artificial Intelligence and Statistics, 1497-1507, 2020
462020
Decentralized Prediction-Correction Methods for Networked Time-Varying Convex Optimization
A Simonetto, A Mokhtari, A Koppel, G Leus, A Ribeiro
IEEE Transactions on Automatic Control 62 (11), 5724-5738, 2017
392017
Direct Runge-Kutta Discretization Achieves Acceleration
J Zhang, A Mokhtari, S Sra, A Jadbabaie
Advances in Neural Information Processing Systems, 3904-3913, 2018
382018
IQN: An incremental quasi-Newton method with local superlinear convergence rate
A Mokhtari, M Eisen, A Ribeiro
SIAM Journal on Optimization 28 (2), 1670-1698, 2018
332018
Conditional gradient method for stochastic submodular maximization: Closing the gap
A Mokhtari, H Hassani, A Karbasi
International Conference on Artificial Intelligence and Statistics, 1886-1895, 2018
292018
Stochastic averaging for constrained optimization with application to online resource allocation
T Chen, A Mokhtari, X Wang, A Ribeiro, GB Giannakis
IEEE Transactions on Signal Processing 65 (12), 3078-3093, 2017
292017
Stochastic conditional gradient methods: From convex minimization to submodular maximization
A Mokhtari, H Hassani, A Karbasi
Journal of Machine Learning Research 21 (105), 1-49, 2020
282020
Network newton-part i: Algorithm and convergence
A Mokhtari, Q Ling, A Ribeiro
arXiv preprint arXiv:1504.06017, 2015
282015
Adaptive Newton method for empirical risk minimization to statistical accuracy
A Mokhtari, H Daneshmand, A Lucchi, T Hofmann, A Ribeiro
Advances in Neural Information Processing Systems (NIPS), 4062-4070, 2016
242016
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
Z Shen, A Mokhtari, T Zhou, P Zhao, H Qian
International Conference on Machine Learning (ICML), 4631-4640, 2018
232018
Surpassing gradient descent provably: A cyclic incremental method with linear convergence rate
A Mokhtari, M Gürbüzbalaban, A Ribeiro
SIAM Journal on Optimization 28 (2), 1420-1447, 2018
23*2018
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Articles 1–20