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News/Quantized Stochastic Primal-Dual Methods for Distributed Optimization under Relaxed Global Geometry
arxiv
PublishedJune 11, 2026 at 4:00 AM

Quantized Stochastic Primal-Dual Methods for Distributed Optimization under Relaxed Global Geometry

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arXiv:2606.11339v1 Announce Type: cross Abstract: We study distributed optimization with stochastic gradients and finite-bit communication modeled by random (unbiased) quantization. We propose q-PDGD, a quantized stochastic primal-dual method, and analyze it under relaxed global geometry. Under rest

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