4 papers · 1 filter
Adaptive Stochastic Natural Gradient Method for Safe Optimization on Binary Space
Kento Uchida, Ryoki Hamano, Masahiro Nomura +1
Optimization problems in real-world applications across the medical and engineering domains often involve potential risks when evaluating candidate solutions. Safe optimization aim…
Diversified Residual Symbolic Regression
Koki Ikeda, Masahiro Nomura, Ryoki Hamano
Symbolic regression (SR) aims to discover explicit mathematical expressions that explain observed data and is widely used in domains where interpretability is essential. Because in…
Multi-start Optimization Method via Scalarization based on Target Point-based Tchebycheff Distance for Multi-objective Optimization
Kota Nagakane, Masahiro Nomura, Isao Ono
Multi-objective optimization is crucial in scientific and industrial applications where solutions must balance trade-offs among conflicting objectives. State-of-the-art methods, su…
A Memetic Algorithm based on Variational Autoencoder for Black-Box Discrete Optimization with Epistasis among Parameters
Aoi Kato, Kenta Kojima, Masahiro Nomura +1
Black-box discrete optimization (BB-DO) problems arise in many real-world applications, such as neural architecture search and mathematical model estimation. A key challenge in BB-…