Research map / Federated learning and privacy / Communication-efficient FL

Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization

NeurIPS 2023 · Federated learning and privacy › Communication-efficient FL · approach: Federated optimization algorithms · 5 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.

Closest papers by meaning

• Solving a Class of Non-Convex Minimax Optimization in Federated Learning (NeurIPS 2023 · similarity 0.91)
• Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization (ICLR 2025 · similarity 0.91)
• Achieving Linear Speedup in Non-IID Federated Bilevel Learning (ICML 2023 · similarity 0.91)
• First-Order Federated Bilevel Learning (AAAI 2025 · similarity 0.90)
• Federated Optimization with Doubly Regularized Drift Correction (ICML 2024 · similarity 0.89)
• Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees (ICLR 2025 · similarity 0.89)