TACC algorithm for adaptive multi-fidelity bandits with improving proxies achieves instance-dependent regret by replacing logarithmic high-fidelity pulls with bounded low-fidelity continuation for intermediate arms.
Ucb-type algorithm for budget-constrained expert learning.arXiv preprint arXiv:2510.22654
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Beyond Static Bias: Adaptive Multi-Fidelity Bandits with Improving Proxies
TACC algorithm for adaptive multi-fidelity bandits with improving proxies achieves instance-dependent regret by replacing logarithmic high-fidelity pulls with bounded low-fidelity continuation for intermediate arms.