3 citations · 3 across the 5 of their papers we have counts for
6 papers
Best-Arm Identification-Based Trust Region Selection for Bayesian Optimization on Multimodal Functions
Nobuo Namura, Sho Takemori
Gaussian process-based Bayesian optimization (BO) is a popular approach for expensive black-box optimization, but its performance often degrades on complex multimodal or high-dimen…
Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization
Nobuo Namura, Sho Takemori
Real-world optimization problems often involve complex objective functions with costly evaluations. While Bayesian optimization (BO) with Gaussian processes is effective for these…
Training-Free Time-Series Anomaly Detection: Leveraging Image Foundation Models
Nobuo Namura, Yuma Ichikawa
Recent advancements in time-series anomaly detection have relied on deep learning models to handle the diverse behaviors of time-series data. However, these models often suffer fro…
Single and Multi-Objective Optimization Benchmark Problems Focusing on Human-Powered Aircraft Design
Nobuo Namura
The landscapes of real-world optimization problems can vary strongly depending on the application. In engineering design optimization, objective functions and constraints are often…
Surrogate-Assisted Reference Vector Adaptation to Various Pareto Front Shapes for Many-Objective Bayesian Optimization
Nobuo Namura
We propose a surrogate-assisted reference vector adaptation (SRVA) method to solve expensive multi- and many-objective optimization problems with various Pareto front shapes. SRVA…
Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation
Nobuo Namura, Tatsuya Hasebe
Brainstorming is an effective technique for offline ideation although the number of participants able to join an ideation session and suggest ideas is limited. To increase the dive…