Research map / Bandits and online learning / Online convex optimization and games
Online Convex Optimization with Unconstrained Domains and Losses
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Remove hyperparameter tuning: use RescaledExp (hyperparameter-free) instead of tuned Adam/AdaGrad/SGD | unknown-L_max unconstrained OCO on CNNs · CIFAR-10 CNN | validation accuracy: 84% vs 84/83/85% | No clear effect |
| Re-center on previous prediction point instead of resetting w to zero when L_t updates | RescaledExp · CNN training | validation accuracy | No clear effect |
| Hyperparameter-free RescaledExp vs. tuned baselines on linear hinge-loss classification (8 datasets) | linear classification · libsvm datasets | average loss after one pass | Mixed |
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