1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
Yuma Ichikawa, Yamato Arai
Learning-based methods have gained attention as general-purpose solvers due to their ability to automatically learn problem-specific heuristics, reducing the need for manually craf…
cs.LG2024★ 1 cited
Statistical Mechanics of Min-Max Problems
Yuma Ichikawa, Koji Hukushima
Min-max optimization problems, also known as saddle point problems, have attracted significant attention due to their applications in various fields, such as fair beamforming, gene…