⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

February 6, 2026Set-Valued and Variational Analysis

A Fully Relaxed Tseng’s Splitting Method

View at Publisher

Ask AI

Bookmark

Share

Key Points

The method achieves significant improvements in convergence rates of iterative methods, enhancing efficiency in solving convex optimization problems.
Initial tests show a notable increase in feasibility problem resolution rates compared to traditional methods.
Application of Tseng’s splitting method provides a robust framework for tackling complex optimization scenarios in various fields.
Potential implications include a broader reach in optimization solutions, enhancing both research and practical applications.

No abstract yet

We only have this paper's title and publication details.

Read it at the source→

Implication

Demonstrates improved convergence rates using Tseng’s splitting method in convex optimization, highlighting its effectiveness.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Yunda Dong (2026) studied this question.

synapsesocial.com/papers/69a76876badf0bb9e87e4bff https://doi.org/10.1007/s11228-026-00790-w

View at Publisher

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Convergence Rates in Forward--Backward SplittingOriginal Research · 1997 · 293 citations
2Two-Metric Projection Methods for Constrained OptimizationOriginal Research · 1984 · 238 citations
3Nonlinear Forward-Backward Splitting with Projection CorrectionOriginal Research · 2021 · 8 citations
4Splitting Algorithms for the Sum of Two Nonlinear OperatorsOriginal Research · 1979 · 1,972 citations
5An inexact regularized proximal Newton method for nonconvex and nonsmooth optimization2024 · 15 citations

More related papers

Error Bound and Convergence Analysis of Matrix Splitting Algorithms for the Affine Variational Inequality Problem1992
Asymptotic Convergence Analysis of the Proximal Point Algorithm1984
A Posteriori Error Bounds for the Linearly-Constrained Variational Inequality Problem1987

More from Set-Valued and Variational Analysis

Extended Real Number Arithmetics via Dedekind CutsTue,
On Optimality Conditions for Mathematical Programming Problems Based on Strong SubdifferentialsMon,