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Near-Optimal Convex Optimization with Lazy Second-Order Oracles

This paper studies the complexity of convex optimization using lazy second-order oracles (Doikov, Chayti, and Jaggi, ICML 2023), where an algorithm queries gradients every iteration and Hessians once per $m$ iterations.

By Xinliang Zhang, Lesi Chen, Chengchang Liu, Jingzhao ZhangarXiv - stat.ML

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Originally published by arXiv - stat.ML on Oct 5, 2026.

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