On ergodicity of the SAGA-LD algorithm

Miklós Rásonyi

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arXiv · 2604.12815

On ergodicity of the SAGA-LD algorithm

Miklós Rásonyi

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Abstract

The so-called SAGA-LD algorithm is used for efficient sampling from high-dimensional distributions in machine learning. Its intricate dynamics resists standard approaches of Markov chain theory. We prove, using a model-specific method, that SAGA-LD converges to a limiting distribution and a law of large numbers holds.

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Miklós Rásonyi. 2026-04-14. On ergodicity of the SAGA-LD algorithm. https://arxiv.org/abs/2604.12815

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