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cs.LG2026
StructZO: Structured Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning
Xuanlin Yang, Jia Li, Zhouchen Lin
Fine-tuning large language models at scale is increasingly limited by the memory cost of backpropagation. Zeroth-Order (ZO) optimizers reduce this burden by relying only on forward…
cs.LG2026
SpecGradFilter: A Spectral Gradient Filtering Framework for Taming Federated Heterogeneity
Liyang Yuan, Yibo Yang, Dandan Guo +2
Federated Learning (FL) is fundamentally challenged by statistical heterogeneity, where non-identically distributed (non-IID) data induces client drift that severely hampers global…
math.OC2026
Near-Optimal Lower Bounds for Randomized Algorithms in Exact Value Zeroth-Order Convex Optimization
Haihan Zhang, Chenheng Zhang, Zhiquan Qi +1
Whether exact scalar feedback intrinsically incurs the additional dimension paid by known zeroth-order methods remains open even for Lipschitz convex optimization. For a univer…