Aryan Mokhtari
Orcid: 0000-0001-6603-0091
According to our database1,
Aryan Mokhtari
authored at least 123 papers
between 2013 and 2024.
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Bibliography
2024
Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models.
Trans. Mach. Learn. Res., 2024
Convergence Analysis of Adaptive Gradient Methods under Refined Smoothness and Noise Assumptions.
CoRR, 2024
CoRR, 2024
In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness.
CoRR, 2024
An Accelerated Gradient Method for Simple Bilevel Optimization with Convex Lower-level Problem.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
IEEE Trans. Inf. Theory, November, 2023
Math. Program., 2023
Limited-Memory Greedy Quasi-Newton Method with Non-asymptotic Superlinear Convergence Rate.
CoRR, 2023
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing and Neural Networks with Quadratic Activations.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the IEEE INFOCOM 2023, 2023
Meta-Learning for Image-Guided Millimeter-Wave Beam Selection in Unseen Environments.
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity.
IEEE J. Sel. Areas Inf. Theory, 2022
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems.
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Conference on Lifelong Learning Agents, 2022
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks.
Proceedings of the 8th IEEE International Conference on Collaboration and Internet Computing, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
High-Dimensional Nonconvex Stochastic Optimization by Doubly Stochastic Successive Convex Approximation.
IEEE Trans. Signal Process., 2020
Convergence Rate of 풪(1/k) for Optimistic Gradient and Extragradient Methods in Smooth Convex-Concave Saddle Point Problems.
SIAM J. Optim., 2020
Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization.
SIAM J. Optim., 2020
J. Mach. Learn. Res., 2020
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization.
J. Mach. Learn. Res., 2020
CoRR, 2020
Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning.
CoRR, 2020
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
IEEE Trans. Signal Process., 2019
IEEE Trans. Signal Process., 2019
SIAM J. Optim., 2019
Proximal Point Approximations Achieving a Convergence Rate of O(1/k) for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE.
Proceedings of the 2019 American Control Conference, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Surpassing Gradient Descent Provably: A Cyclic Incremental Method with Linear Convergence Rate.
SIAM J. Optim., 2018
SIAM J. Optim., 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Parallel Stochastic Successive Convex Approximation Method for Large-Scale Dictionary Learning.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation.
IEEE Trans. Signal Process., 2017
Decentralized Prediction-Correction Methods for Networked Time-Varying Convex Optimization.
IEEE Trans. Autom. Control., 2017
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Large-scale nonconvex stochastic optimization by Doubly Stochastic Successive Convex approximation.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
A double incremental aggregated gradient method with linear convergence rate for large-scale optimization.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017
2016
IEEE Trans. Signal Process., 2016
DQM: Decentralized Quadratically Approximated Alternating Direction Method of Multipliers.
IEEE Trans. Signal Process., 2016
A Decentralized Second-Order Method with Exact Linear Convergence Rate for Consensus Optimization.
IEEE Trans. Signal Inf. Process. over Networks, 2016
J. Mach. Learn. Res., 2016
CoRR, 2016
CoRR, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Decentralized constrained consensus optimization with primal dual splitting projection.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
A Quasi-newton prediction-correction method for decentralized dynamic convex optimization.
Proceedings of the 15th European Control Conference, 2016
Proceedings of the 55th IEEE Conference on Decision and Control, 2016
Online optimization in dynamic environments: Improved regret rates for strongly convex problems.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016
Proceedings of the 55th IEEE Conference on Decision and Control, 2016
Proceedings of the 2016 American Control Conference, 2016
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
2015
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
Decentralized quadratically approximated alternating direction method of multipliers.
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015
A decentralized prediction-correction method for networked time-varying convex optimization.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
2014
Proceedings of the IEEE International Conference on Acoustics, 2014
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014
2013
Proceedings of the 14th IEEE Workshop on Signal Processing Advances in Wireless Communications, 2013
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013