Similar Items
Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods
by: Park, Chanwoong, et al.
Published: (2024)
by: Park, Chanwoong, et al.
Published: (2024)
Technical Report: A Totally Asynchronous Nesterov's Accelerated Gradient Method for Convex Optimization
by: Pond, Ellie, et al.
Published: (2024)
by: Pond, Ellie, et al.
Published: (2024)
Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations
by: Liu, Jun
Published: (2026)
by: Liu, Jun
Published: (2026)
Formally Verified Physics-Informed Neural Control Lyapunov Functions
by: Liu, Jun, et al.
Published: (2024)
by: Liu, Jun, et al.
Published: (2024)
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
by: Chen, Jun, et al.
Published: (2023)
by: Chen, Jun, et al.
Published: (2023)
Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification
by: Liu, Jun, et al.
Published: (2023)
by: Liu, Jun, et al.
Published: (2023)
Anytime Acceleration of Gradient Descent
by: Zhang, Zihan, et al.
Published: (2024)
by: Zhang, Zihan, et al.
Published: (2024)
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)
LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction
by: Liu, Jun, et al.
Published: (2024)
by: Liu, Jun, et al.
Published: (2024)
Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks
by: Xu, Zhenghao, et al.
Published: (2024)
by: Xu, Zhenghao, et al.
Published: (2024)
EMA-Nesterov: Stabilizing Nesterov's Lookahead for Accelerated Deep Learning Optimization
by: Yau, Chung-Yiu, et al.
Published: (2026)
by: Yau, Chung-Yiu, et al.
Published: (2026)
Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization
by: Borodich, Ekaterina, et al.
Published: (2025)
by: Borodich, Ekaterina, et al.
Published: (2025)
A Passivity-Based Method for Accelerated Convex Optimisation
by: Cho, Namhoon, et al.
Published: (2023)
by: Cho, Namhoon, et al.
Published: (2023)
Inference of Online Newton Methods with Nesterov's Accelerated Sketching
by: Wang, Haoxuan, et al.
Published: (2026)
by: Wang, Haoxuan, et al.
Published: (2026)
(Un)supervised Learning of Maximal Lyapunov Functions
by: Barreau, Matthieu, et al.
Published: (2024)
by: Barreau, Matthieu, et al.
Published: (2024)
Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking
by: Chen, Jun, et al.
Published: (2025)
by: Chen, Jun, et al.
Published: (2025)
Model-Free Output Feedback Stabilization via Policy Gradient Methods
by: Zhang, Ankang, et al.
Published: (2026)
by: Zhang, Ankang, et al.
Published: (2026)
Nesterov Accelerated Distributed Optimization with Efficient Quantized Communication
by: Wu, Ruochen, et al.
Published: (2026)
by: Wu, Ruochen, et al.
Published: (2026)
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2023)
by: Ding, Dongsheng, et al.
Published: (2023)
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
by: Chakrabarti, Kushal, et al.
Published: (2021)
by: Chakrabarti, Kushal, et al.
Published: (2021)
Iterative Pre-Conditioning for Expediting the Gradient-Descent Method: The Distributed Linear Least-Squares Problem
by: Chakrabarti, Kushal, et al.
Published: (2020)
by: Chakrabarti, Kushal, et al.
Published: (2020)
Distributionally Robust Policy and Lyapunov-Certificate Learning
by: Long, Kehan, et al.
Published: (2024)
by: Long, Kehan, et al.
Published: (2024)
A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints
by: Wang, Lei, et al.
Published: (2022)
by: Wang, Lei, et al.
Published: (2022)
Nesterov Acceleration for Ensemble Kalman Inversion and Variants
by: Vernon, Sydney, et al.
Published: (2025)
by: Vernon, Sydney, et al.
Published: (2025)
Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
by: Long, Kehan, et al.
Published: (2025)
by: Long, Kehan, et al.
Published: (2025)
On the Gradient Domination of the LQG Problem
by: Fallah, Kasra, et al.
Published: (2025)
by: Fallah, Kasra, et al.
Published: (2025)
Safe Gradient Flow for Bilevel Optimization
by: Sharifi, Sina, et al.
Published: (2025)
by: Sharifi, Sina, et al.
Published: (2025)
Unified Lyapunov Method for ISS of PDEs: A Tutorial on Constructing Generalized Lyapunov Functionals for Parabolic and Hyperbolic Equations
by: Zheng, Jun, et al.
Published: (2026)
by: Zheng, Jun, et al.
Published: (2026)
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning
by: Chakrabarti, Kushal, et al.
Published: (2022)
by: Chakrabarti, Kushal, et al.
Published: (2022)
Near-optimal Closed-loop Method via Lyapunov Damping for Convex Optimization
by: Maier, Severin, et al.
Published: (2023)
by: Maier, Severin, et al.
Published: (2023)
Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks
by: Liao, Fangshuo, et al.
Published: (2023)
by: Liao, Fangshuo, et al.
Published: (2023)
Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
by: Keane, Ronan
Published: (2024)
by: Keane, Ronan
Published: (2024)
Enhancing Convergence of Decentralized Gradient Tracking under the KL Property
by: Chen, Xiaokai, et al.
Published: (2024)
by: Chen, Xiaokai, et al.
Published: (2024)
Accelerated forward-backward and Douglas-Rachford splitting dynamics
by: Ozaslan, Ibrahim K., et al.
Published: (2024)
by: Ozaslan, Ibrahim K., et al.
Published: (2024)
Almost Sure Convergence Analysis of Differentially Private Stochastic Gradient Methods
by: Mukherjee, Amartya, et al.
Published: (2025)
by: Mukherjee, Amartya, et al.
Published: (2025)
YuriiFormer: A Suite of Nesterov-Accelerated Transformers
by: Zimin, Aleksandr, et al.
Published: (2026)
by: Zimin, Aleksandr, et al.
Published: (2026)
Converse Barrier Functions via Lyapunov Functions
by: Liu, Jun
Published: (2020)
by: Liu, Jun
Published: (2020)
Gradient-Informed Monte Carlo Fine-Tuning of Diffusion Models for Low-Thrust Trajectory Design
by: Graebner, Jannik, et al.
Published: (2025)
by: Graebner, Jannik, et al.
Published: (2025)
Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
by: Serry, Mohamed, et al.
Published: (2026)
by: Serry, Mohamed, et al.
Published: (2026)
Lyapunov Function Consistent Adaptive Network Signal Control with Back Pressure and Reinforcement Learning
by: Ma, Chaolun, et al.
Published: (2022)
by: Ma, Chaolun, et al.
Published: (2022)
Similar Items
-
Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods
by: Park, Chanwoong, et al.
Published: (2024) -
Technical Report: A Totally Asynchronous Nesterov's Accelerated Gradient Method for Convex Optimization
by: Pond, Ellie, et al.
Published: (2024) -
Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations
by: Liu, Jun
Published: (2026) -
Formally Verified Physics-Informed Neural Control Lyapunov Functions
by: Liu, Jun, et al.
Published: (2024) -
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
by: Chen, Jun, et al.
Published: (2023)