Bregman-divergence-based Arimoto-Blahut algorithm
<|reference_start|>Bregman-divergence-based Arimoto-Blahut algorithm: We generalize the generalized Arimoto-Blahut algorithm to a general function defined over Bregman-divergence system. In existing methods, when linear constraints are imposed, each iteration needs to solve a convex minimization. Exploiting our obtained algorithm, we propose a convex-optimization-free algorithm. This algorithm can be applied to classical and quantum rate-distortion theory. We numerically apply our method to the derivation of the optimal conditional distribution in the rate-distortion theory.<|reference_end|>
@article{hayashi2024bregman-divergence-based,
    title={Bregman-divergence-based Arimoto-Blahut algorithm},
    author={Masahito Hayashi},
    journal={arXiv preprint arXiv:2408.05454},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.05454},
    primaryClass={math.OC cs.IT math.IT quant-ph}
}