AI Paper Atlas

Research map / Optimization / Nonconvex and smooth optimization

Adaptive Three Operator Splitting

ICML 2018 · Optimization › Nonconvex and smooth optimization · approach: Adaptive first-order convex methods · 7 citations (OpenAlex)

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 changedWhereMeasuredEffect
Use Adaptive TOS Variant 2 with growing step sizes instead of fixed-step-size methodsAdaptive TOS · 12 optimization experimentscomputational performance: best performing on 10 out of 12 experimentsHelped
Use Adaptive TOS Variant 2 with growing step sizes instead of fixed-step-size methodsAdaptive TOS · Low-regularization experimentstime to convergence: on 3 out of 6 the adaptive TOS is an order of magnitude fasterHelped
Use Adaptive TOS Variant 2 with growing step sizes instead of fixed-step-size methodsAdaptive TOS · High-regularization experimentstime to convergence: never more than a factor 2.6Helped
Allow the step size to grow (Variant 2) rather than only decrease or remain fixed (Variant 1) (ablation)Adaptive TOS · Optimization benchmarkscomputational performanceHelped
Apply adaptive step sizes to smooth terms with non-uniform rather than uniform curvatureAdaptive TOS · Optimization benchmarkscomputational performanceHelped
Use Adaptive TOS Variant 2 rather than other compared methodsAdaptive TOS · Experiments E and Hcomputational performanceNo clear effect

Closest papers by meaning

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.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy