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math.OC2026
Adaptive Normalized Gradient Method for -smooth Problems: Estimating Problem Parameters as a Region
Rikiya Okazaki, Shotaro Yagishita, Hideitsu Hino
We propose a parameter-free and efficient gradient descent algorithm for -smooth optimization. This notion of smoothness, introduced by Zhang et al. (2020), allows the s…
math.OC2026
A proximal gradient method with adaptive backtracking for weakly smooth multiobjective optimization
Yuki Miyazaki, Masaru Ito, Shotaro Yagishita
In this paper, we propose a proximal gradient method with adaptive linesearch for multiobjective optimization problems whose objective functions are weakly smooth, i.e., they have…