Kazuto Fukuchi

According to our database, Kazuto Fukuchi authored at least 40 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Convergence Rate of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions.

Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

IEEE Trans. Evol. Comput., April, 2024

Behavior-Targeted Attack on Reinforcement Learning with Limited Access to Victim's Policy.

Shojiro Yamabe, Kazuto Fukuchi, Ryoma Senda, Jun Sakuma

CoRR, 2024

Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift.

Mitsuhiro Fujikawa, Yohei Akimoto, Jun Sakuma, Kazuto Fukuchi

CoRR, 2024

Adversarial Attacks on Hidden Tasks in Multi-Task Learning.

Yu Zhe, Rei Nagaike, Daiki Nishiyama, Kazuto Fukuchi, Jun Sakuma

CoRR, 2024

Linear Convergence Rate Analysis of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions.

Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

Statistically Significant Pattern Mining With Ordinal Utility.

Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

IEEE Trans. Knowl. Data Eng., September, 2023

Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and Its Application to Berthing Control Tasks.

Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

ACM Trans. Evol. Learn. Optim., June, 2023

CAMRI Loss: Improving the Recall of a Specific Class without Sacrificing Accuracy.

Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

IEICE Trans. Inf. Syst., April, 2023

Adaptive scenario subset selection for worst-case optimization and its application to well placement optimization.

Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Appl. Soft Comput., January, 2023

Unauthorized AI cannot recognize me: Reversible adversarial example.

Jiayang Liu, Weiming Zhang, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

Pattern Recognit., 2023

Certified Defense for Content Based Image Retrieval.

Kazuya Kakizaki, Kazuto Fukuchi, Jun Sakuma

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Demographic Parity Constrained Minimax Optimal Regression under Linear Model.

Kazuto Fukuchi, Jun Sakuma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs.

Kaiwen Xu, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Privformer: Privacy-preserving Transformer with MPC.

Yoshimasa Akimoto, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

2022

Locally Differentially Private Minimum Finding.

Kazuto Fukuchi, Chia-Mu Yu, Jun Sakuma

IEICE Trans. Inf. Syst., August, 2022

Convergence rate of the (1+1)-evolution strategy on locally strongly convex functions with lipschitz continuous gradient and their monotonic transformations.

Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

CoRR, 2022

Domain Generalization via Adversarially Learned Novel Domains.

Yu Zhe, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

IEEE Access, 2022

Explicitly Constrained Black-Box Optimization With Disconnected Feasible Domains Using Deep Generative Models.

Naoki Sakamoto, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

IEEE Access, 2022

Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification.

Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning.

Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the International Joint Conference on Neural Networks, 2022

Did You Use My GAN to Generate Fake? Post-hoc Attribution of GAN Generated Images via Latent Recovery.

Syou Hirofumi, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

Proceedings of the International Joint Conference on Neural Networks, 2022

Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximation.

Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

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

Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Level generation for angry birds with sequential VAE and latent variable evolution.

Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Convergence rate of the (1+1)-evolution strategy with success-based step-size adaptation on convex quadratic functions.

Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Adaptive scenario subset selection for min-max black-box continuous optimization.

Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020

Deep generative model for non-convex constraint handling.

Naoki Sakamoto, Eiji Semmatsu, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Faking Fairness via Stealthily Biased Sampling.

Kazuto Fukuchi, Satoshi Hara, Takanori Maehara

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Locally Differentially Private Minimum Finding.

Kazuto Fukuchi, Chia-Mu Yu, Arashi Haishima, Jun Sakuma

CoRR, 2019

Pretending Fair Decisions via Stealthily Biased Sampling.

Kazuto Fukuchi, Satoshi Hara, Takanori Maehara

CoRR, 2019

2018

Minimax Optimal Additive Functional Estimation with Discrete Distribution.

Kazuto Fukuchi, Jun Sakuma

CoRR, 2018

Minimax Optimal Additive Functional Estimation with Discrete Distribution: Slow Divergence Speed Case.

Kazuto Fukuchi, Jun Sakuma

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

Minimax optimal estimators for additive scalar functionals of discrete distributions.

Kazuto Fukuchi, Jun Sakuma

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Differentially Private Chi-squared Test by Unit Circle Mechanism.

Kazuya Kakizaki, Kazuto Fukuchi, Jun Sakuma

Proceedings of the 34th International Conference on Machine Learning, 2017

Differentially Private Empirical Risk Minimization with Input Perturbation.

Kazuto Fukuchi, Quang Khai Tran, Jun Sakuma

Proceedings of the Discovery Science - 20th International Conference, 2017

2015

Prediction with Model-Based Neutrality.

Kazuto Fukuchi, Toshihiro Kamishima, Jun Sakuma

IEICE Trans. Inf. Syst., 2015

Differentially Private Analysis of Outliers.

Rina Okada, Kazuto Fukuchi, Kazuya Kakizaki, Jun Sakuma

CoRR, 2015

Fairness-Aware Learning with Restriction of Universal Dependency using f-Divergences.

Kazuto Fukuchi, Jun Sakuma

CoRR, 2015

Differentially Private Analysis of Outliers.

Rina Okada, Kazuto Fukuchi, Jun Sakuma

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014

Neutralized Empirical Risk Minimization with Generalization Neutrality Bound.

Kazuto Fukuchi, Jun Sakuma

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014