activity
20212026
most citedSurrogate-Assisted Reference Vector Adaptation to Various Pareto Front Shapes for Many-Objective Bayesian Optimization

3 citations · 5 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Transporting Unsecured Stacked Payloads with a Quadrupedal Robot via Multi-Objective Reinforcement Learning

Nobuo Namura, Masayuki Hiromoto, Kento Uemura +2

Transporting unsecured payloads with legged robots over uneven terrain requires balancing locomotion performance and payload stability, since aggressive motion can destabilize the…

cs.LG2026

Trajectory-Aware Best-Arm Identification for Local Search Allocation in Bayesian Optimization and Beyond

Nobuo Namura, Sho Takemori

Bayesian optimization (BO) is effective for expensive black-box optimization, but its performance often degrades on multimodal or high-dimensional problems. A promising remedy is t…

cs.LG2024

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…

cs.LG2024

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…

cs.NE2023★ 2 cited

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…

cs.LG2021★ 3 cited

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…

cs.HC2021

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…