Jun Sakuma

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 100

Top Venues

Publications

Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Convergence Rate of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions. IEEE Trans. Evol. Comput. 28 (2) (2024)
Yu Zhe, Jun Sakuma
Parameter Matching Attack: Enhancing Practical Applicability of Availability Attacks. CoRR (2024)
Yu Zhe, Rei Nagaike, Daiki Nishiyama, Kazuto Fukuchi, Jun Sakuma
Adversarial Attacks on Hidden Tasks in Multi-Task Learning. CoRR (2024)
Mitsuhiro Fujikawa, Yohei Akimoto, Jun Sakuma, Kazuto Fukuchi
Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift. CoRR (2024)
Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Linear Convergence Rate Analysis of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions. GECCO Companion (2024)
Yuwei Sun, Ippei Fujisawa, Arthur Juliani, Jun Sakuma, Ryota Kanai
Remembering Transformer for Continual Learning. CoRR (2024)
Yuwei Sun, Hideya Ochiai, Jun Sakuma
Attacking-Distance-Aware Attack: Semi-targeted Model Poisoning on Federated Learning. IEEE Trans. Artif. Intell. 5 (2) (2024)
Shojiro Yamabe, Kazuto Fukuchi, Ryoma Senda, Jun Sakuma
Behavior-Targeted Attack on Reinforcement Learning with Limited Access to Victim's Policy. CoRR (2024)
Yu Zhe, Jun Sakuma
Zero-shot domain adaptation based on dual-level mix and contrast. CoRR (2024)
Kaiwen Xu, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs. CoRR (2023)
Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and Its Application to Berthing Control Tasks. ACM Trans. Evol. Learn. Optim. 3 (2) (2023)
Kazuya Kakizaki, Kazuto Fukuchi, Jun Sakuma
Certified Defense for Content Based Image Retrieval. WACV (2023)
Kaiwen Xu, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs. IJCAI (2023)
Junki Mori, Ryo Furukawa, Isamu Teranishi, Jun Sakuma
Heterogeneous Domain Adaptation with Positive and Unlabeled Data. BigData (2023)
Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning. CoRR (2023)
Yoshimasa Akimoto, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Privformer: Privacy-preserving Transformer with MPC. EuroS&P (2023)
Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
CAMRI Loss: Improving the Recall of a Specific Class without Sacrificing Accuracy. IEICE Trans. Inf. Syst. 106 (4) (2023)
Joshua Butke, Noriaki Hashimoto, Ichiro Takeuchi, Hiroaki Miyoshi, Koichi Ohshima, Jun Sakuma
Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping. MLMI@MICCAI (2) (2023)
Kazuto Fukuchi, Jun Sakuma
Demographic Parity Constrained Minimax Optimal Regression under Linear Model. NeurIPS (2023)
Yuwei Sun, Hideya Ochiai, Jun Sakuma
Instance-level Trojan Attacks on Visual Question Answering via Adversarial Learning in Neuron Activation Space. CoRR (2023)
Junki Mori, Ryo Furukawa, Isamu Teranishi, Jun Sakuma
Heterogeneous Domain Adaptation with Positive and Unlabeled Data. CoRR (2023)
Joshua Butke, Noriaki Hashimoto, Ichiro Takeuchi, Hiroaki Miyoshi, Koichi Ohshima, Jun Sakuma
Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping. CoRR (2023)
Jiayang Liu, Weiming Zhang, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Unauthorized AI cannot recognize me: Reversible adversarial example. Pattern Recognit. 134 (2023)
Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Adaptive scenario subset selection for worst-case optimization and its application to well placement optimization. Appl. Soft Comput. 133 (2023)
Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Statistically Significant Pattern Mining With Ordinal Utility. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and its Application to Berthing Control Tasks. CoRR (2023)
Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy. IJCNN (2022)
Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Unsupervised Causal Binary Concepts Discovery with VAE for Black-Box Model Explanation. AAAI (2022)
Kazuto Fukuchi, Chia-Mu Yu, Jun Sakuma
Locally Differentially Private Minimum Finding. IEICE Trans. Inf. Syst. (8) (2022)
Naoki Sakamoto, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Explicitly Constrained Black-Box Optimization With Disconnected Feasible Domains Using Deep Generative Models. IEEE Access 10 (2022)
Yuwei Sun, Hideya Ochiai, Jun Sakuma
Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis. CoRR (2022)
Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximation. GECCO (2022)
Yuwei Sun, Hideya Ochiai, Jun Sakuma
Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis. IJCNN (2022)
Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning. IJCNN (2022)
Syou Hirofumi, Kazuto Fukuchi, Yohei Akimoto, Jun Sakuma
Did You Use My GAN to Generate Fake? Post-hoc Attribution of GAN Generated Images via Latent Recovery. IJCNN (2022)
Daiki Nishiyama, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy. CoRR (2022)
Yu Zhe, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Domain Generalization via Adversarially Learned Novel Domains. IEEE Access 10 (2022)
Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification. NeurIPS (2022)
Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Adaptive Scenario Subset Selection for Worst-Case Optimization and its Application to Well Placement Optimization. CoRR (2022)
Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Convergence rate of the (1+1)-evolution strategy on locally strongly convex functions with lipschitz continuous gradient and their monotonic transformations. CoRR (2022)
Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification. CoRR (2022)
Yu Zhe, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Domain Generalization Via Adversarially Learned Novel Domains. ICME (2022)
Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Black-Box Min-Max Continuous Optimization Using CMA-ES with Worst-case Ranking Approximation. CoRR (2022)
Rei Sato, Jun Sakuma, Youhei Akimoto
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment. AAAI (2021)
Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Level Generation for Angry Birds with Sequential VAE and Latent Variable Evolution. CoRR (2021)
Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Adaptive scenario subset selection for min-max black-box continuous optimization. GECCO (2021)
Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation. CoRR (2021)
Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions. CoRR (2021)
Taiga Ono, Takeshi Sugawara, Jun Sakuma, Tatsuya Mori
Application of Adversarial Examples to Physical ECG Signals. CoRR (2021)
Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Convergence rate of the (1+1)-evolution strategy with success-based step-size adaptation on convex quadratic functions. GECCO (2021)
Kazuya Kakizaki, Taiki Miyagawa, Inderjeet Singh, Jun Sakuma
Toward Practical Adversarial Attacks on Face Verification Systems. BIOSIG (2021)
Takumi Tanabe, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Level generation for angry birds with sequential VAE and latent variable evolution. GECCO (2021)
Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Statistically Significant Pattern Mining with Ordinal Utility. CoRR (2020)
Hiromu Yakura, Youhei Akimoto, Jun Sakuma
Generate (Non-Software) Bugs to Fool Classifiers. AAAI (2020)
Naoki Sakamoto, Eiji Semmatsu, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
Deep generative model for non-convex constraint handling. GECCO (2020)
Thien Q. Tran, Jun Sakuma
Seasonal-adjustment Based Feature Selection Method for Large-scale Search Engine Logs. CoRR (2020)
Rei Sato, Jun Sakuma, Youhei Akimoto
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment. CoRR (2020)
Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma
Statistically Significant Pattern Mining with Ordinal Utility. KDD (2020)
Thien Q. Tran, Jun Sakuma
Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs. KDD (2019)
Kazuto Fukuchi, Chia-Mu Yu, Arashi Haishima, Jun Sakuma
Locally Differentially Private Minimum Finding. CoRR (2019)
Hiromu Yakura, Shinnosuke Shinozaki, Reon Nishimura, Yoshihiro Oyama, Jun Sakuma
Neural malware analysis with attention mechanism. Comput. Secur. 87 (2019)
Ryota Namba, Jun Sakuma
Robust Watermarking of Neural Network with Exponential Weighting. CoRR (2019)
Hiromu Yakura, Youhei Akimoto, Jun Sakuma
Generate (non-software) Bugs to Fool Classifiers. CoRR (2019)
Ryota Namba, Jun Sakuma
Robust Watermarking of Neural Network with Exponential Weighting. AsiaCCS (2019)
Hiromu Yakura, Jun Sakuma
Robust Audio Adversarial Example for a Physical Attack. IJCAI (2019)
Hiroyuki Hanada, Toshiyuki Takada, Jun Sakuma, Ichiro Takeuchi
Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values. CoRR (2018)
Kazuto Fukuchi, Jun Sakuma
Minimax Optimal Additive Functional Estimation with Discrete Distribution: Slow Divergence Speed Case. ISIT (2018)
Hiroaki Kikuchi, Takayasu Yamaguchi, Koki Hamada, Yuji Yamaoka, Hidenobu Oguri, Jun Sakuma
Study on Record Linkage of Anonymizied Data. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (1) (2018)
Jun Sakuma, Tatsuya Osame
Recommendation with k-Anonymized Ratings. Trans. Data Priv. 11 (1) (2018)
Wenjie Lu, Jun-Jie Zhou, Jun Sakuma
Non-interactive and Output Expressive Private Comparison from Homomorphic Encryption. AsiaCCS (2018)
Takao Murakami, Hideitsu Hino, Jun Sakuma
Toward Distribution Estimation under Local Differential Privacy with Small Samples. Proc. Priv. Enhancing Technol. 2018 (3) (2018)
Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma
Recommendation Independence. FAT (2018)
Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma
Model-based and actual independence for fairness-aware classification. Data Min. Knowl. Discov. 32 (1) (2018)
Hiromu Yakura, Jun Sakuma
Robust Audio Adversarial Example for a Physical Attack. CoRR (2018)
Kazuto Fukuchi, Jun Sakuma
Minimax Optimal Additive Functional Estimation with Discrete Distribution: Slow Divergence Speed Case. CoRR (2018)
Kazuto Fukuchi, Jun Sakuma
Minimax Optimal Additive Functional Estimation with Discrete Distribution. CoRR (2018)
Hiroyuki Hanada, Atsushi Shibagaki, Jun Sakuma, Ichiro Takeuchi
Efficiently Monitoring Small Data Modification Effect for Large-Scale Learning in Changing Environment. AAAI (2018)
Noboru Kunihiro, Wenjie Lu, Takashi Nishide, Jun Sakuma
Outsourced Private Function Evaluation with Privacy Policy Enforcement. TrustCom/BigDataSE (2018)
Hiromu Yakura, Shinnosuke Shinozaki, Reon Nishimura, Yoshihiro Oyama, Jun Sakuma
Malware Analysis of Imaged Binary Samples by Convolutional Neural Network with Attention Mechanism. CODASPY (2018)
Wenjie Lu, Jun Sakuma
More Practical Privacy-Preserving Machine Learning as A Service via Efficient Secure Matrix Multiplication. WAHC@CCS (2018)
Tatsuki Koga, Naoki Nonaka, Jun Sakuma, Jun Seita
General-to-Detailed GAN for Infrequent Class Medical Images. CoRR (2018)
Kazuto Fukuchi, Quang Khai Tran, Jun Sakuma
Differentially Private Empirical Risk Minimization with Input Perturbation. CoRR (2017)
Kazuya Kakizaki, Kazuto Fukuchi, Jun Sakuma
Differentially Private Chi-squared Test by Unit Circle Mechanism. ICML (2017)
Xu Long, Jun Sakuma
Differentially Private Semi-Supervised Classification. SMARTCOMP (2017)
Keita Emura, Takuya Hayashi, Noboru Kunihiro, Jun Sakuma
Mis-operation Resistant Searchable Homomorphic Encryption. AsiaCCS (2017)
Kosuke Kusano, Ichiro Takeuchi, Jun Sakuma
Privacy-preserving and Optimal Interval Release for Disease Susceptibility. AsiaCCS (2017)
Hiromu Yakura, Shinnosuke Shinozaki, Reon Nishimura, Yoshihiro Oyama, Jun Sakuma
Malware Analysis of Imaged Binary Samples by Convolutional Neural Network with Attention Mechanism. AISec@CCS (2017)
Kazuto Fukuchi, Quang Khai Tran, Jun Sakuma
Differentially Private Empirical Risk Minimization with Input Perturbation. DS (2017)
Jun Sakuma, Tatsuya Osame
Recommendation with k-anonymized Ratings. CoRR (2017)
Takahito Kaiho, Wenjie Lu, Toshiyuki Amagasa, Jun Sakuma
Towards Privacy-Preserving Record Linkage with Record-Wise Linkage Policy. DEXA (1) (2017)
Kazuto Fukuchi, Jun Sakuma
Minimax Optimal Estimators for Additive Scalar Functionals of Discrete Distributions. CoRR (2017)
Wenjie Lu, Shohei Kawasaki, Jun Sakuma
Using Fully Homomorphic Encryption for Statistical Analysis of Categorical, Ordinal and Numerical Data. NDSS (2017)
Kazuto Fukuchi, Jun Sakuma
Minimax optimal estimators for additive scalar functionals of discrete distributions. ISIT (2017)
Hiroyuki Hanada, Atsushi Shibagaki, Jun Sakuma, Ichiro Takeuchi
Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization. CoRR (2016)
Toshiyuki Takada, Hiroyuki Hanada, Yoshiji Yamada, Jun Sakuma, Ichiro Takeuchi
Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization. ACML (2016)
Tadanori Teruya, Yoshiki Aoki, Jun Sakuma
Fairy ring: Ubiquitous secure multiparty computation framework for smartphone applications. ISITA (2016)
Wenjie Lu, Shohei Kawasaki, Jun Sakuma
Using Fully Homomorphic Encryption for Statistical Analysis of Categorical, Ordinal and Numerical Data. IACR Cryptol. ePrint Arch. 2016 (2016)
Hiroaki Kikuchi, Takayasu Yamaguchi, Koki Hamada, Yuji Yamaoka, Hidenobu Oguri, Jun Sakuma
A Study from the Data Anonymization Competition Pwscup 2015. DPM/QASA@ESORICS (2016)
Toshiyuki Takada, Hiroyuki Hanada, Yoshiji Yamada, Jun Sakuma, Ichiro Takeuchi
Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization. CoRR (2016)
Hiroaki Kikuchi, Takayasu Yamaguchi, Koki Hamada, Yuji Yamaoka, Hidenobu Oguri, Jun Sakuma
Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization. AINA (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jun Sakuma