Research map / Optimization / Nonconvex and smooth optimization
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Discretize the high-resolution NAG-SC ODE with symplectic Euler rather than explicit Euler (ablation) | NAG-SC ODE · Strongly convex smooth functions | objective gap convergence rate: 1 + \frac{1}{9} \sqrt{ \frac{\mu}{L} } -> 1 - \frac{\mu}{80L} | Helped |
| Discretize the high-resolution NAG-SC ODE with implicit Euler rather than symplectic Euler (ablation) | NAG-SC ODE · Strongly convex smooth functions | objective gap convergence rate: 1 + \frac{1}{9} \sqrt{ \frac{\mu}{L} } -> 1 + \frac{1}{4} \sqrt{\frac{\mu}{L}} | No clear effect |
| Retain the high-resolution gradient-correction term when using symplectic Euler (ablation) | Strongly convex NAG-SC discretization · Strongly convex smooth functions | objective gap convergence rate: 1 + \frac{1}{9} \sqrt{ \frac{\mu}{L} } -> 1 + \frac{\mu}{16L} | Helped |
| Discretize the heavy-ball ODE with implicit Euler instead of symplectic Euler (ablation) | Heavy-ball ODE · Strongly convex smooth functions | objective gap convergence rate: 1 + \frac{\mu}{16L} -> 1 + \frac{1}{4} \sqrt{\frac{\mu}{L}} | Helped |
| Discretize the modified high-resolution NAG-C ODE with symplectic Euler | NAG-C ODE · Smooth convex functions | objective gap convergence rate: O(1/k^2) | Helped |
| Use explicit Euler on the modified high-resolution NAG-C ODE (ablation) | NAG-C ODE · Smooth convex functions | convergence | Hurt |
Closest papers by meaning
- Direct Runge-Kutta Discretization Achieves Acceleration (NeurIPS 2018 · similarity 0.88)
- Conformal Symplectic and Relativistic Optimization (NeurIPS 2020 · similarity 0.88)
- Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems (ICML 2022 · similarity 0.87)
- Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis (ICML 2022 · similarity 0.86)
- A Variational Perspective on High-Resolution ODEs (NeurIPS 2023 · similarity 0.86)
- Accelerated Over-Relaxation Heavy-Ball Method: Achieving Global Accelerated Convergence with Broad Generalization (ICLR 2025 · similarity 0.83)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
