19 citations · 19 across the 4 of their papers we have counts for
5 papers
On the Generalization Bounds of Symbolic Regression with Genetic Programming
Masahiro Nomura, Ryoki Hamano, Isao Ono
Symbolic regression (SR) with genetic programming (GP) aims to discover interpretable mathematical expressions directly from data. Despite its strong empirical success, the theoret…
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-…
RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
Yukinari Hisaki, Isao Ono
In this paper, we propose an off-policy deep reinforcement learning (DRL) method utilizing the average reward criterion. While most existing DRL methods employ the discounted rewar…
CMA-ES with Learning Rate Adaptation
Masahiro Nomura, Youhei Akimoto, Isao Ono
The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most successful methods for solving continuous black-box optimization problems. A practically useful aspe…