Research map / Continual learning / Online and replay-based
Look-ahead Meta Learning for Continual Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add learned per-parameter asynchronous rates for meta-updates (ablation) | C-MAML · CIFAR-100 Multiple-Pass | RA: 65.44 { $\pm$ 0.99} -> \textbf{70.08 { $\pm$ 0.66}} | Helped |
| add learned per-parameter asynchronous rates for meta-updates (ablation) | C-MAML · CIFAR-100 Single-Pass | RA: 55.57 { $\pm$ 0.94} -> \textbf{61.18 { $\pm$ 1.44}} | Helped |
| add learned per-parameter asynchronous rates for meta-updates (ablation) | C-MAML · TinyImagenet Multiple-Pass | RA: 61.93 { $\pm$ 1.55} -> \textbf{66.99 { $\pm$ 1.65}} | Helped |
| add learned per-parameter asynchronous rates for meta-updates (ablation) | C-MAML · TinyImagenet Single-Pass | RA: 48.77 { $\pm$ 1.26} -> 52.59 { $\pm$ 1.35} | Helped |
| make learned meta-update rates asynchronous rather than fixed (ablation) | Sync · CIFAR-100 Multiple-Pass | RA: 67.06 { $\pm$ 0.62} -> \textbf{70.08 { $\pm$ 0.66}} | Helped |
| make learned meta-update rates asynchronous rather than fixed (ablation) | Sync · CIFAR-100 Single-Pass | RA: 58.99 { $\pm$ 1.40} -> \textbf{61.18 { $\pm$ 1.44}} | Helped |
| make learned meta-update rates asynchronous rather than fixed (ablation) | Sync · TinyImagenet Multiple-Pass | RA: 65.40 { $\pm$ 1.40} -> \textbf{66.99 { $\pm$ 1.65}} | Helped |
| make learned meta-update rates asynchronous rather than fixed (ablation) | Sync · TinyImagenet Single-Pass | RA: \textbf{52.84 { $\pm$ 2.55}} -> 52.59 { $\pm$ 1.35} | No clear effect |
| add meta-learning to LR-modulated ER updates (ablation) | La-ER · CIFAR-100 Multiple-Pass | RA: 67.17 { $\pm$ 1.14} -> \textbf{70.08 { $\pm$ 0.66}} | Helped |
| add meta-learning to LR-modulated ER updates (ablation) | La-ER · TinyImagenet Multiple-Pass | RA: 54.76 { $\pm$ 1.94} -> \textbf{66.99 { $\pm$ 1.65}} | Helped |
| add meta-learning to LR-modulated ER updates (ablation) | La-ER · TinyImagenet Single-Pass | RA: 44.75 { $\pm$ 1.96} -> 52.59 { $\pm$ 1.35} | Helped |
| add asynchronous LR modulation (ablation) | C-MAML · MNIST Permutations | RA: \textbf{74.54 { $\pm$ 0.54}} -> 74.34 { $\pm$ 0.67} | No clear effect |
Closest papers by meaning
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- Trust Region Continual Learning as an Implicit Meta-Learner (NeurIPS 2026 · similarity 0.87)
- Re-evaluating Continual Learning with Few-Shot Adaptation (NeurIPS 2026 · similarity 0.87)
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