Saved in:
| Main Authors: | Chen, Shi, Li, Qin, Tse, Oliver, Wright, Stephen J. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.04006 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
by: Li, Shuyao, et al.
Published: (2023)
by: Li, Shuyao, et al.
Published: (2023)
Towards Weaker Variance Assumptions for Stochastic Optimization
by: Alacaoglu, Ahmet, et al.
Published: (2025)
by: Alacaoglu, Ahmet, et al.
Published: (2025)
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
by: Alacaoglu, Ahmet, et al.
Published: (2024)
by: Alacaoglu, Ahmet, et al.
Published: (2024)
A new perspective on low-rank optimization
by: Bertsimas, Dimitris, et al.
Published: (2021)
by: Bertsimas, Dimitris, et al.
Published: (2021)
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
by: Li, Huan, et al.
Published: (2021)
by: Li, Huan, et al.
Published: (2021)
First-ish Order Methods: Hessian-aware Scalings of Gradient Descent
by: Smee, Oscar, et al.
Published: (2025)
by: Smee, Oscar, et al.
Published: (2025)
Non-geodesically-convex optimization in the Wasserstein space
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
by: Kwon, Jeongyeol, et al.
Published: (2023)
by: Kwon, Jeongyeol, et al.
Published: (2023)
Accelerated Parameter-Free Stochastic Optimization
by: Kreisler, Itai, et al.
Published: (2024)
by: Kreisler, Itai, et al.
Published: (2024)
Worst-case generation via minimax optimization in Wasserstein space
by: Cheng, Xiuyuan, et al.
Published: (2025)
by: Cheng, Xiuyuan, et al.
Published: (2025)
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
by: Lowy, Andrew, et al.
Published: (2024)
by: Lowy, Andrew, et al.
Published: (2024)
Stochastic Subspace Descent Accelerated via Bi-fidelity Line Search
by: Cheng, Nuojin, et al.
Published: (2025)
by: Cheng, Nuojin, et al.
Published: (2025)
Derivative-free tree optimization for complex systems
by: Wei, Ye, et al.
Published: (2024)
by: Wei, Ye, et al.
Published: (2024)
Accelerating Decentralized Optimization via Overlapping Local Steps
by: Zhou, Yijie, et al.
Published: (2026)
by: Zhou, Yijie, et al.
Published: (2026)
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
by: Lee, Ching-pei, et al.
Published: (2022)
by: Lee, Ching-pei, et al.
Published: (2022)
Stochastic global optimization of continuous functions via random walks on Grassmannians
by: Gupta, Kartik, et al.
Published: (2026)
by: Gupta, Kartik, et al.
Published: (2026)
Nesterov Acceleration for Ensemble Kalman Inversion and Variants
by: Vernon, Sydney, et al.
Published: (2025)
by: Vernon, Sydney, et al.
Published: (2025)
Learning solutions to some toy constrained optimization problems in infinite dimensional Hilbert spaces
by: Mandal, Pinak
Published: (2024)
by: Mandal, Pinak
Published: (2024)
Learning to optimize: A tutorial for continuous and mixed-integer optimization
by: Chen, Xiaohan, et al.
Published: (2024)
by: Chen, Xiaohan, et al.
Published: (2024)
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
A survey on secure decentralized optimization and learning
by: Liu, Changxin, et al.
Published: (2024)
by: Liu, Changxin, et al.
Published: (2024)
A simple uniformly optimal method without line search for convex optimization
by: Li, Tianjiao, et al.
Published: (2023)
by: Li, Tianjiao, et al.
Published: (2023)
Anytime Acceleration of Gradient Descent
by: Zhang, Zihan, et al.
Published: (2024)
by: Zhang, Zihan, et al.
Published: (2024)
A successive approximation method in functional spaces for hierarchical optimal control problems and its application to learning
by: Befekadu, Getachew K.
Published: (2024)
by: Befekadu, Getachew K.
Published: (2024)
Continuous-time reinforcement learning for optimal switching over multiple regimes
by: Huang, Yijie, et al.
Published: (2025)
by: Huang, Yijie, et al.
Published: (2025)
Accelerated Nonnegative Tensor Completion via Integer Programming
by: Pan, Wenhao, et al.
Published: (2022)
by: Pan, Wenhao, et al.
Published: (2022)
Provable Acceleration of Nesterov's Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks
by: Liu, Xin, et al.
Published: (2022)
by: Liu, Xin, et al.
Published: (2022)
Distributed Learning over Arbitrary Topology: Linear Speed-Up with Polynomial Transient Time
by: You, Runze, et al.
Published: (2025)
by: You, Runze, et al.
Published: (2025)
Local adapt-then-combine algorithms for distributed nonsmooth optimization: Achieving provable communication acceleration
by: Guo, Luyao, et al.
Published: (2026)
by: Guo, Luyao, et al.
Published: (2026)
Manifold learning and optimization using tangent space proxies
by: Robinett, Ryan A., et al.
Published: (2025)
by: Robinett, Ryan A., et al.
Published: (2025)
What price to pay? Auto-tuning a building MPC controller for optimal economic cost
by: Yu, Jiarui, et al.
Published: (2025)
by: Yu, Jiarui, et al.
Published: (2025)
An inexact Bregman proximal point method and its acceleration version for unbalanced optimal transport
by: Chen, Xiang, et al.
Published: (2024)
by: Chen, Xiang, et al.
Published: (2024)
Stability Regularized Cross-Validation
by: Cory-Wright, Ryan, et al.
Published: (2025)
by: Cory-Wright, Ryan, et al.
Published: (2025)
Compact Lifted Relaxations for Low-Rank Optimization
by: Cory-Wright, Ryan, et al.
Published: (2026)
by: Cory-Wright, Ryan, et al.
Published: (2026)
SHANG++: Robust Stochastic Acceleration under Multiplicative Noise
by: Yu, Yaxin, et al.
Published: (2026)
by: Yu, Yaxin, et al.
Published: (2026)
DCatalyst: A Unified Accelerated Framework for Decentralized Optimization
by: Cao, Tianyu, et al.
Published: (2025)
by: Cao, Tianyu, et al.
Published: (2025)
Accelerating Single-Pass SGD for Generalized Linear Prediction
by: Chen, Qian, et al.
Published: (2026)
by: Chen, Qian, et al.
Published: (2026)
The Optimality of (Accelerated) SGD for High-Dimensional Quadratic Optimization
by: Zhang, Haihan, et al.
Published: (2024)
by: Zhang, Haihan, et al.
Published: (2024)
Accelerated Fully First-Order Methods for Bilevel and Minimax Optimization
by: Li, Chris Junchi
Published: (2024)
by: Li, Chris Junchi
Published: (2024)
Similar Items
-
A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
by: Li, Shuyao, et al.
Published: (2023) -
Towards Weaker Variance Assumptions for Stochastic Optimization
by: Alacaoglu, Ahmet, et al.
Published: (2025) -
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
by: Alacaoglu, Ahmet, et al.
Published: (2024) -
A new perspective on low-rank optimization
by: Bertsimas, Dimitris, et al.
Published: (2021) -
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)