Research map / Optimization / Nonconvex and smooth optimization
Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| increase threads from 1 to 20 in ASVRG-wild (ablation) | ASVRG-wild · MNIST | iteration speedup: 1 -> 19.28 | Helped |
| increase threads from 1 to 20 in ASVRG-wild (ablation) | ASVRG-wild · MNIST | running time speedup: 1 -> 12.58 | Helped |
| increase threads from 1 to 20 in ASVRG-wild (ablation) | ASVRG-wild · CIFAR10 | running time speedup: 1 -> 14.53 | Helped |
| variance-reduced asynchronous updates (ASVRG) instead of ASGD | asynchronous nonconvex optimization · synthetic 5-layer NN, 8/12/20 cores | gradient norm vs time | Mixed |
Closest papers by meaning
- Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization (AAAI 2017 · similarity 0.93)
- Fast Asynchronous Parallel Stochastic Gradient Descent: A Lock-Free Approach with Convergence Guarantee (AAAI 2016 · similarity 0.93)
- Stochastic Variance Reduction for Nonconvex Optimization (ICML 2016 · similarity 0.91)
- Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization (NeurIPS 2018 · similarity 0.91)
- Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization (NeurIPS 2017 · similarity 0.90)
- Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity (ICML 2025 · similarity 0.88)
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