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Aryan Mokhtari
Aryan Mokhtari
austin.utexas.edu의 이메일 확인됨 - 홈페이지
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Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach.
A Fallah, A Mokhtari, AE Ozdaglar
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
1002*2020
Fedpaq: A communication-efficient federated learning method with periodic averaging and quantization
A Reisizadeh, A Mokhtari, H Hassani, A Jadbabaie, R Pedarsani
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020
5912020
Exploiting Shared Representations for Personalized Federated Learning
L Collins, H Hassani, A Mokhtari, S Shakkottai
International Conference on Machine Learning (ICML), 2021
3342021
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 (AISTATS …, 2020
3022020
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
2232016
Global Convergence of Online Limited Memory BFGS
A Mokhtari, A Ribeiro
Journal of Machine Learning Research 16, 3151-3181, 2015
2142015
On the convergence theory of gradient-based model-agnostic meta-learning algorithms
A Fallah, A Mokhtari, A Ozdaglar
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020
2062020
Federated learning with compression: Unified analysis and sharp guarantees
F Haddadpour, MM Kamani, A Mokhtari, M Mahdavi
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021
1962021
RES: Regularized Stochastic BFGS Algorithm
A Mokhtari, A Ribeiro
IEEE Transactions on Signal Processing 62 (23), 6089-6104, 2014
1862014
DSA: Decentralized double stochastic averaging gradient algorithm
A Mokhtari, A Ribeiro
The Journal of Machine Learning Research 17 (1), 2165-2199, 2016
1812016
Network Newton Distributed Optimization Methods
A Mokhtari, Q Ling, A Ribeiro
IEEE Transactions on Signal Processing 65 (1), 146-161, 2017
1792017
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
1312016
Convergence rate of O (1/k) for optimistic gradient and extra-gradient methods in smooth convex-concave saddle point problems
A Mokhtari, A Ozdaglar, S Pattathil
SIAM Journal on Optimization 30 (4), 3230-3251, 2020
129*2020
Decentralized Quasi-Newton Methods
M Eisen, A Mokhtari, A Ribeiro
IEEE Transactions on Signal Processing 65 (10), 2613 - 2628, 2017
1262017
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
1262016
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
1212016
An exact quantized decentralized gradient descent algorithm
A Reisizadeh, A Mokhtari, H Hassani, R Pedarsani
IEEE Transactions on Signal Processing 67 (19), 4934-4947, 2019
1182019
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
1122020
Direct Runge-Kutta Discretization Achieves Acceleration
J Zhang, A Mokhtari, S Sra, A Jadbabaie
Advances in Neural Information Processing Systems (NeurIPS), 2018
1102018
Robust and communication-efficient collaborative learning
A Reisizadeh, H Taheri, A Mokhtari, H Hassani, R Pedarsani
Advances in Neural Information Processing Systems (NeurIPS), 2019
942019
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학술자료 1–20