activity
20152022
most citedLevel Generation for Angry Birds with Sequential VAE and Latent Variable Evolution

9 citations · 23 across the 10 of their papers we have counts for

collaborators

12 papers

cs.NE2022

Adaptive Scenario Subset Selection for Worst-Case Optimization and its Application to Well Placement Optimization

Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma +1

In this study, we consider simulation-based worst-case optimization problems with continuous design variables and a finite scenario set. To reduce the number of simulations require…

cs.NE20222 cited

Black-Box Min--Max Continuous Optimization Using CMA-ES with Worst-case Ranking Approximation

Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma +1

In this study, we investigate the problem of min-max continuous optimization in a black-box setting . A popular approach updates and simultaneously…

cs.LG2021

Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation

Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto +1

We aim to explain a black-box classifier with the form: `data X is classified as class Y because X \textit{has} A, B and \textit{does not have} C' in which A, B, and C are high-lev…

cs.AI20219 cited

Level Generation for Angry Birds with Sequential VAE and Latent Variable Evolution

Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma +1

Video game level generation based on machine learning (ML), in particular, deep generative models, has attracted attention as a technique to automate level generation. However, app…

cs.NE2021

Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions

Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma +1

The (1+1)-evolution strategy (ES) with success-based step-size adaptation is analyzed on a general convex quadratic function and its monotone transformation, that is, $f(x) = g((x…

stat.ME20207 cited

Statistically Significant Pattern Mining with Ordinal Utility

Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto +1

Statistically significant patterns mining (SSPM) is an essential and challenging data mining task in the field of knowledge discovery in databases (KDD), in which each pattern is e…