Research map / Optimization / Nonconvex and smooth optimization
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders
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.
Closest papers by meaning
- Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient (ICML 2024 · similarity 0.87)
- Demystifying SGD with Doubly Stochastic Gradients (ICML 2024 · similarity 0.87)
- Efficient Continual Finite-Sum Minimization (ICLR 2024 · similarity 0.86)
- Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion (NeurIPS 2024 · similarity 0.86)
- Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems (ICML 2025 · similarity 0.85)
- Faster Sampling via Stochastic Gradient Proximal Sampler (ICML 2024 · similarity 0.85)
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.