5 citations · 5 across the 4 of their papers we have counts for
4 papers
Sparse Signal Recovery Using Log-Sum Regularization and Adaptive Smoothing
Keisuke Morita, Masayuki Ohzeki
We study sparse signal recovery from noisy linear observations using nonconvex log-sum regularization. The log-sum penalty reduces the shrinkage bias of regularization and…
Phase transition in compressed sensing using log-sum penalty and adaptive smoothing
Keisuke Morita, Federico Ricci-Tersenghi, Masayuki Ohzeki
In many real-world problems, recovering sparse signals from underdetermined linear systems remains a fundamental challenge. Although norm minimization is widely used, it s…
Filtering out mislabeled training instances using black-box optimization and quantum annealing
Makoto Otsuka, Kento Kodama, Keisuke Morita +1
This study proposes an approach for removing mislabeled instances from contaminated training datasets by combining surrogate model-based black-box optimization (BBO) with postproce…
Random Postprocessing for Combinatorial Bayesian Optimization
Keisuke Morita, Yoshihiko Nishikawa, Masayuki Ohzeki
Model-based sequential approaches to discrete "black-box" optimization, including Bayesian optimization techniques, often access the same points multiple times for a given objectiv…