FunctionApproximation Throughout thepaper,weassume access totwofunction classesQ (S A R)andW (S A R). Todevelop intuition, theyare supposed to modelQπ and wπ/µ, respectively, though most of our main results are stated without assuming any kind of realizability.

FunctionApproximation Throughout thepaper,weassume access totwofunction classesQ (S A R)andW (S A R). Todevelop intuition, theyare supposed to modelQπ and wπ/µ, respectively, though most of our main results are stated without assuming any kind of realizability.

Sparsified Online Newton (SONew) method, a memory-efficient second-order algorithm that yields a sparsified yet effective preconditioner.

It is worth noting that the contribution of IFSL is orthogonal to existing fine-tuning and meta-learning based FSL methods, hence IFSL can improveallofthem,achievinganew1-/5-shot state-of-the-art onminiImageNet, tieredImageNet, andcross-domain CUB.

Despite its simplicity, guaranteeing efficiency andwhether sampling theactions fromtheposterior could leadtounbounded future trajectories is unknown.

Large language models (LLMs) have achieved a remarkable performance on diverse tasks across multiple domains, as reported in recent surveys [Wei et al., 2022, Bubeck et al., 2023].