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Rieoptax: Riemannian Optimization in JAX - MaRDI portal

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Rieoptax: Riemannian Optimization in JAX

From MaRDI portal
Publication:6413476

arXiv2210.04840MaRDI QIDQ6413476

Author name not available (Why is that?)

Publication date: 10 October 2022

Abstract: We present Rieoptax, an open source Python library for Riemannian optimization in JAX. We show that many differential geometric primitives, such as Riemannian exponential and logarithm maps, are usually faster in Rieoptax than existing frameworks in Python, both on CPU and GPU. We support various range of basic and advanced stochastic optimization solvers like Riemannian stochastic gradient, stochastic variance reduction, and adaptive gradient methods. A distinguishing feature of the proposed toolbox is that we also support differentially private optimization on Riemannian manifolds.




Has companion code repository: https://github.com/saitejautpala/rieoptax








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