← Authors

Aryan Mokhtari

54 papers · 2015–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (15) 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🏠 Conference Loyalist (22) πŸ”¬ Deep Specialist (30) 🀝 Dynamic Duo (14) πŸ† Keyword Champion (2) πŸ“ˆ Trend Setter ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (65) πŸ’Ž Century Club (54) πŸ”₯ Unstoppable (11)

Conferences

NIPS (22) AISTATS (14) ICML (8) COLT (4) JMLR (4) ICLR (1) UAI (1)

Top co-authors

Hamed Hassani (14) Ruichen Jiang (11) Sanjay Shakkottai (8) Alejandro Ribeiro (7) Liam Collins (7) Asuman Ozdaglar (7) Amin Karbasi (6) Qiujiang Jin (5) Ali Jadbabaie (4) Alireza Fallah (4)

Keywords

convex optimization (10) stochastic optimization (8) convergence rate (7) superlinear convergence (6) empirical risk minimization (6) quasi-newton method (6) hessian approximation (5) gradient descent (5) communication efficiency (5) saddle point (5) adaptive sample size (5) decentralized optimization (5) federated learning (4) representation learning (4) model-agnostic meta-learning (4) distributed learning (4) nonconvex optimization (3) strongly convex (3) stochastic gradient descent (3) submodular optimization (3)

Papers

Learning Mixtures of Experts with EM: A Mirror Descent Perspective ICML 2025
On the Crucial Role of Initialization for Matrix Factorization ICLR 2025
Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization COLT 2025
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search NIPS 2024
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks ICML 2024
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate AISTATS 2024
In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness NIPS 2024
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization NIPS 2024
Stochastic Newton Proximal Extragradient Method NIPS 2024
An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization NIPS 2024
Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization NIPS 2023
Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence COLT 2023
InfoNCE Loss Provably Learns Cluster-Preserving Representations COLT 2023
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem AISTATS 2023
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem NIPS 2023
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing NIPS 2023
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems UAI 2022
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning NIPS 2022
Minimax Optimization: The Case of Convex-Submodular AISTATS 2022
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance COLT 2022
MAML and ANIL Provably Learn Representations ICML 2022
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood ICML 2022
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning NIPS 2021
Exploiting Shared Representations for Personalized Federated Learning ICML 2021
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach NIPS 2021
Federated Learning with Compression: Unified Analysis and Sharp Guarantees AISTATS 2021
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks NIPS 2021
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization AISTATS 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy AISTATS 2020
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free AISTATS 2020
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning JMLR 2020
Task-Robust Model-Agnostic Meta-Learning NIPS 2020
Submodular Meta-Learning NIPS 2020
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach NIPS 2020
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking NIPS 2020
One Sample Stochastic Frank-Wolfe AISTATS 2020
Quantized Decentralized Stochastic Learning over Directed Graphs ICML 2020
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms AISTATS 2020
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach AISTATS 2020
DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate AISTATS 2020
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match NIPS 2019
Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods AISTATS 2019
Robust and Communication-Efficient Collaborative Learning NIPS 2019
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication ICML 2018
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings ICML 2018
Escaping Saddle Points in Constrained Optimization NIPS 2018
Direct Runge-Kutta Discretization Achieves Acceleration NIPS 2018
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method AISTATS 2018
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap AISTATS 2018
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization NIPS 2017
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NIPS 2016
DSA: Decentralized Double Stochastic Averaging Gradient Algorithm JMLR 2016
Global Convergence of Online Limited Memory BFGS JMLR 2015