近接分離最適化アルゴリズムと深層学習の融合について

抄録

Optimization tools have been extensively employed in signal processing. Recent advances in optimization algorithms based on proximity operators have broadened the application range of optimization-based signal processing. Moreover, deep learning has rapidly developed a new signal processing scheme that can perform notably better than conventional ones. Consequently, they have been combined in some studies. In this paper, we briefly review studies combining proximal splitting algorithms and deep learning.