Accelerating Optimization via Differentiable Stopping Time
Fuente:
arXiv
Saved in:
| Main Authors: | Xie, Zhonglin, Fong, Yiman, Yuan, Haoran, Wen, Zaiwen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ODE-based Learning to Optimize
by: Xie, Zhonglin, et al.
Published: (2024)
by: Xie, Zhonglin, et al.
Published: (2024)
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation
by: Ke, Zhifa, et al.
Published: (2023)
by: Ke, Zhifa, et al.
Published: (2023)
Non-Asymptotic Global Convergence of PPO-Clip
by: Liu, Yin, et al.
Published: (2025)
by: Liu, Yin, et al.
Published: (2025)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023)
by: Li, Tianyou, et al.
Published: (2023)
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
by: Ke, Zhifa, et al.
Published: (2024)
by: Ke, Zhifa, et al.
Published: (2024)
Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time
by: Fu, Qiang, et al.
Published: (2025)
by: Fu, Qiang, et al.
Published: (2025)
Constructing Industrial-Scale Optimization Modeling Benchmark
by: Li, Zhong, et al.
Published: (2026)
by: Li, Zhong, et al.
Published: (2026)
Accelerated Optimization Landscape of Linear-Quadratic Regulator
by: Feng, Lechen, et al.
Published: (2023)
by: Feng, Lechen, et al.
Published: (2023)
Accelerated Natural Gradient Method for Parametric Manifold Optimization
by: Li, Chenyi, et al.
Published: (2025)
by: Li, Chenyi, et al.
Published: (2025)
Learning to Stop: Deep Learning for Mean Field Optimal Stopping
by: Magnino, Lorenzo, et al.
Published: (2024)
by: Magnino, Lorenzo, et al.
Published: (2024)
Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
by: Mehmood, Sheheryar, et al.
Published: (2024)
by: Mehmood, Sheheryar, et al.
Published: (2024)
Accelerated Distributed Optimization with Compression and Error Feedback
by: Gao, Yuan, et al.
Published: (2025)
by: Gao, Yuan, et al.
Published: (2025)
Safe Reinforcement Learning for Constrained Markov Decision Processes with Stochastic Stopping Time
by: Mazumdar, Abhijit, et al.
Published: (2024)
by: Mazumdar, Abhijit, 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)
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
by: Li, Huan, et al.
Published: (2021)
by: Li, Huan, et al.
Published: (2021)
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
by: Jiang, Wei, et al.
Published: (2024)
by: Jiang, Wei, et al.
Published: (2024)
Deep Learning for the Multiple Optimal Stopping Problem
by: Laurière, Mathieu, et al.
Published: (2025)
by: Laurière, Mathieu, et al.
Published: (2025)
DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
by: Pal, Shraman, et al.
Published: (2026)
by: Pal, Shraman, et al.
Published: (2026)
Accelerated Parameter-Free Stochastic Optimization
by: Kreisler, Itai, et al.
Published: (2024)
by: Kreisler, Itai, et al.
Published: (2024)
Unified Precision-Guaranteed Stopping Rules for Contextual Learning
by: Ding, Mingrui, et al.
Published: (2026)
by: Ding, Mingrui, et al.
Published: (2026)
Accelerating Multi-Block Constrained Optimization Through Learning to Optimize
by: Liang, Ling, et al.
Published: (2024)
by: Liang, Ling, et al.
Published: (2024)
Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spaces
by: Zhu, Linglingzhi, et al.
Published: (2024)
by: Zhu, Linglingzhi, et al.
Published: (2024)
Differentially Private Optimization with Sparse Gradients
by: Ghazi, Badih, et al.
Published: (2024)
by: Ghazi, Badih, et al.
Published: (2024)
From PowerSGD to PowerSGD+: Low-Rank Gradient Compression for Distributed Optimization with Convergence Guarantees
by: Xie, Shengping, et al.
Published: (2025)
by: Xie, Shengping, et al.
Published: (2025)
A General and Streamlined Differentiable Optimization Framework
by: Rosemberg, Andrew W., et al.
Published: (2025)
by: Rosemberg, Andrew W., et al.
Published: (2025)
The Error in Multivariate Linear Extrapolation with Applications to Derivative-Free Optimization
by: Cao, Liyuan, et al.
Published: (2023)
by: Cao, Liyuan, et al.
Published: (2023)
On Regularization via Early Stopping for Least Squares Regression
by: Sonthalia, Rishi, et al.
Published: (2024)
by: Sonthalia, Rishi, et al.
Published: (2024)
DCatalyst: A Unified Accelerated Framework for Decentralized Optimization
by: Cao, Tianyu, et al.
Published: (2025)
by: Cao, Tianyu, et al.
Published: (2025)
The Optimality of (Accelerated) SGD for High-Dimensional Quadratic Optimization
by: Zhang, Haihan, et al.
Published: (2024)
by: Zhang, Haihan, et al.
Published: (2024)
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
by: Hu, Jie, et al.
Published: (2024)
by: Hu, Jie, et al.
Published: (2024)
Feed m Birds with One Scone: Accelerating Multi-task Gradient Balancing via Bi-level Optimization
by: Chen, Xuxing, et al.
Published: (2026)
by: Chen, Xuxing, et al.
Published: (2026)
Differential Privacy via Distributionally Robust Optimization
by: Selvi, Aras, et al.
Published: (2023)
by: Selvi, Aras, et al.
Published: (2023)
Gradient-Variation Online Adaptivity for Accelerated Optimization with Hölder Smoothness
by: Zhao, Yuheng, et al.
Published: (2025)
by: Zhao, Yuheng, et al.
Published: (2025)
Accelerated Rates between Stochastic and Adversarial Online Convex Optimization
by: Sachs, Sarah, et al.
Published: (2023)
by: Sachs, Sarah, et al.
Published: (2023)
An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization
by: Cao, Jincheng, et al.
Published: (2024)
by: Cao, Jincheng, et al.
Published: (2024)
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
by: Gong, Xiaochuan, et al.
Published: (2024)
by: Gong, Xiaochuan, 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)
Scalable Acceleration for Classification-Based Derivative-Free Optimization
by: Han, Tianyi, et al.
Published: (2023)
by: Han, Tianyi, et al.
Published: (2023)
Optimal Parameter Adaptation for Safety-Critical Control via Safe Barrier Bayesian Optimization
by: Wang, Shengbo, et al.
Published: (2025)
by: Wang, Shengbo, et al.
Published: (2025)
Joint Parameter and State-Space Bayesian Optimization: Using Process Expertise to Accelerate Manufacturing Optimization
by: Kiroriwal, Saksham, et al.
Published: (2026)
by: Kiroriwal, Saksham, et al.
Published: (2026)
Similar Items
-
ODE-based Learning to Optimize
by: Xie, Zhonglin, et al.
Published: (2024) -
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation
by: Ke, Zhifa, et al.
Published: (2023) -
Non-Asymptotic Global Convergence of PPO-Clip
by: Liu, Yin, et al.
Published: (2025) -
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023) -
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
by: Ke, Zhifa, et al.
Published: (2024)