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Lookahead Optimizer: k steps forward, 1 step back
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| wrap SGD with Lookahead (k=5, alpha=0.5) and aggressive LR decay | SGD · ImageNet | top-1 accuracy | Helped |
| wrap Adam with Lookahead | Adam · Penn Treebank LSTM | perplexity | Helped |
| wrap Adam with Lookahead | Adam · WMT14 En-De | BLEU | No clear effect |
| vary Lookahead k and alpha (ablation) | Lookahead SGD · CIFAR-100 | validation accuracy | No clear effect |
Closest papers by meaning
- EMA-Nesterov: Stabilizing Nesterov's Lookahead for Accelerated Deep Learning Optimization (NeurIPS 2026 · similarity 0.90)
- Improving Sharpness-Aware Minimization by Lookahead (ICML 2024 · similarity 0.88)
- Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks (NeurIPS 2025 · similarity 0.85)
- Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling (NeurIPS 2024 · similarity 0.85)
- MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent (ICML 2024 · similarity 0.85)
- A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD (ICML 2025 · similarity 0.85)
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