| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| Stochastic Convex Optimization (σ = O(1), N = MKR) | MiniBatch SGD | Convergence Rate Bound1 | 8 | 1mo ago | |
| Distributed Linear System (theoretical) | Convergence Rate1 | 6 | 1mo ago | ||
| Optimization under Byzantine and/or DP adversaries | Byz-SGDM | Utility2 | 6 | 4mo ago | |
| Problem Strongly-convex 2 | Scaffold | Communication Cost2 | 4 | 5mo ago | |
| Problem Nonconvex objective functions | Scaffold | Computational Cost1 | 3 | 5mo ago | |
| Linearly converging algorithms with Partial Participation exact gradients | DIANA-PP | Communication Complexity Bound (UpCom)1 | 1 | 1mo ago | |
| General First-order optimization setting | - | - | 0 | 2mo ago | |
| Nonconvex smooth objectives | - | - | 0 | 5mo ago | |
| μ-strongly convex functions | - | - | 0 | 5mo ago | |
| General convex functions | - | - | 0 | 5mo ago | |
| Strongly convex objective under similarity | - | - | 0 | 5mo ago | |
| General Non-convex Distributed Optimization Theoretical | - | - | 0 | 5mo ago |
