Jun Sakuma

发表

Differentially Private Analysis of Outliers pdf

Jun Sakuma, Kazuto Fukuchi, Rina Okada, 2015, ECML/PKDD.

Fairness-aware Learning through Regularization Approach

Jun Sakuma, Shotaro Akaho, Toshihiro Kamishima, 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

Collusion-resistant privacy-preserving data mining

Hiroshi Nakagawa, Jun Sakuma, Bin Yang, 2010, KDD.

Study on Record Linkage of Anonymizied Data

Jun Sakuma, Yuji Yamaoka, Koki Hamada, 2018, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Recommendation Independence

Jun Sakuma, Shotaro Akaho, Hideki Asoh, 2018, FAT.

Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis

Yuwei Sun, H. Ochiai, Jun Sakuma, 2022, ArXiv.

Message from the BITS 2018 General Chairs and TPC Chairs

Mauro Conti, Jun Sakuma, Atsuko Miyaji, 2018 .

Application of Adversarial Examples to Physical ECG Signals pdf

Jun Sakuma, Takeshi Sugawara, Taiga Ono, 2021, ArXiv.

Deep generative model for non-convex constraint handling

Jun Sakuma, Kazuto Fukuchi, Naoki Sakamoto, 2020, GECCO.

Faster Multiplication Triplet Generation from Homomorphic Encryption for Practical Privacy-Preserving Machine Learning under a Narrow Bandwidth

Jun Sakuma, Wenjie Lu, Jun Sakuma, 2018, IACR Cryptol. ePrint Arch..

Minimax Optimal Fair Regression under Linear Model

Kazuto Fukuchi, Jun Sakuma, 2022, 2206.11546.

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

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

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

Youhei Akimoto, Jun Sakuma, Kazuto Fukuchi, 2021, Annual Conference on Genetic and Evolutionary Computation.

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

Youhei Akimoto, Jun Sakuma, Kazuto Fukuchi, 2021, AAAI.

The Independence of Fairness-Aware Classifiers

Jun Sakuma, Shotaro Akaho, Hideki Asoh, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Fairness-Aware Classifier with Prejudice Remover Regularizer

Jun Sakuma, Shotaro Akaho, Hideki Asoh, 2012, ECML/PKDD.

Jun Sakuma, Shotaro Akaho, Hideki Asoh, 2014, RecSys Posters.

Privacy-preserving search for chemical compound databases

Goichiro Hanaoka, Kiyoshi Asai, Kana Shimizu, 2015, BMC Bioinformatics.

Privacy-Preserving Statistical Analysis by Exact Logistic Regression

Jun Sakuma, Koji Tsuda, David duVerle, 2015, 2015 IEEE Security and Privacy Workshops.

Differentially Private Semi-Supervised Classification

Jun Sakuma, Xu Long, Jun Sakuma, 2017, 2017 IEEE International Conference on Smart Computing (SMARTCOMP).

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

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2022, IEEE Access.

Toward Distribution Estimation under Local Differential Privacy with Small Samples

Jun Sakuma, Hideitsu Hino, Takao Murakami, 2018, Proc. Priv. Enhancing Technol..

Robust Audio Adversarial Example for a Physical Attack

Hiromu Yakura, Jun Sakuma, Jun Sakuma, 2018, IJCAI.

Heterogeneous Domain Adaptation with Positive and Unlabeled Data

Isamu Teranishi, Jun Sakuma, Junki Mori, 2023, 2304.07955.

Neutralized Empirical Risk Minimization with Generalization Neutrality Bound

Jun Sakuma, Kazuto Fukuchi, Kazuto Fukuchi, 2014, ECML/PKDD.

Prediction with Model-Based Neutrality

Jun Sakuma, Toshihiro Kamishima, Kazuto Fukuchi, 2013, ECML/PKDD.

Neural malware analysis with attention mechanism

Hiromu Yakura, Jun Sakuma, Yoshihiro Oyama, 2019, Comput. Secur..

Malware Analysis of Imaged Binary Samples by Convolutional Neural Network with Attention Mechanism

Hiromu Yakura, Jun Sakuma, Yoshihiro Oyama, 2018, CODASPY.

Robust Watermarking of Neural Network with Exponential Weighting

Jun Sakuma, Ryota Namba, Jun Sakuma, 2019, AsiaCCS.

Online Prediction with Privacy

Jun Sakuma, Hiromi Arai, Jun Sakuma, 2010, ICML.

Privacy-Preserving Dose-Response Relationship Test

Jun Sakuma, Hiroaki Kikuchi, Tomoki Sato, 2014, 2014 17th International Conference on Network-Based Information Systems.

Privacy Preserving Semi-supervised Learning for Labeled Graphs

Jun Sakuma, Hiromi Arai, Jun Sakuma, 2011, ECML/PKDD.

Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection

Jun Sakuma, Rebecca N. Wright, Jun Sakuma, 2009, ACML.

More Practical Privacy-Preserving Machine Learning as A Service via Efficient Secure Matrix Multiplication

Jun Sakuma, Wenjie Lu, Jun Sakuma, 2018, WAHC@CCS.

Efficiency Improvement of Neutrality-Enhanced Recommendation

Jun Sakuma, Shotaro Akaho, Hideki Asoh, 2013, Decisions@RecSys.

Efficient Secure Outsourcing of Genome-Wide Association Studies

Jun Sakuma, Wenjie Lu, Yoshiji Yamada, 2015, 2015 IEEE Security and Privacy Workshops.

Differentially Private Chi-squared Test by Unit Circle Mechanism

Jun Sakuma, Kazuto Fukuchi, Kazuya Kakizaki, 2017, ICML.

Efficiently Monitoring Small Data Modification Effect for Large-Scale Learning in Changing Environment

Jun Sakuma, Ichiro Takeuchi, Hiroyuki Hanada, 2018, AAAI.

Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization pdf

Jun Sakuma, Ichiro Takeuchi, Hiroyuki Hanada, 2016, ACML.

Privacy-preservation for Stochastic Gradient Descent Method

Jun Sakuma, Jun Sakuma, Shuang Wu, 2012 .

Enhancement of the Neutrality in Recommendation

Jun Sakuma, Shotaro Akaho, Hideki Asoh, 2012, Decisions@RecSys.

Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption

Jun Sakuma, Yoshiji Yamada, Wen-Jie Lu, 2015, BMC Medical Informatics and Decision Making.

Using Fully Homomorphic Encryption for Statistical Analysis of Categorical, Ordinal and Numerical Data

Jun Sakuma, Wenjie Lu, Shohei Kawasaki, 2016, NDSS.

Differentially Private Empirical Risk Minimization with Input Perturbation pdf

Jun Sakuma, Kazuto Fukuchi, Quang Khai Tran, 2017, DS.

Instance-level Trojan Attacks on Visual Question Answering via Adversarial Learning in Neuron Activation Space

Yuwei Sun, H. Ochiai, Jun Sakuma, 2023, ArXiv.

Non-interactive and Output Expressive Private Comparison from Homomorphic Encryption

Jun Sakuma, Wenjie Lu, Jun-Jie Zhou, 2018, AsiaCCS.

Domain Generalization Via Adversarially Learned Novel Domains

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2022, 2022 IEEE International Conference on Multimedia and Expo (ICME).

Domain Generalization via Adversarially Learned Novel Domains

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2022, IEEE Access.

Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs

Jun Sakuma, Thien Q. Tran, Jun Sakuma, 2019, KDD.

Privformer: Privacy-preserving Transformer with MPC

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2023, European Symposium on Security and Privacy.

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

Youhei Akimoto, Jun Sakuma, Kazuto Fukuchi, 2021, GECCO.

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

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2021, GECCO.

Robust Audio Adversarial Example for a Physical Attack

Jun Sakuma, Hiromu Yakura, 2018, IJCAI.

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

Youhei Akimoto, Kazuto Fukuchi, Jun Sakuma, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values

I. Takeuchi, Jun Sakuma, H. Hanada, 2018, ArXiv.

Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization pdf

Jun Sakuma, Ichiro Takeuchi, Hiroyuki Hanada, 2016, ArXiv.

Oblivious Evaluation of Non-deterministic Finite Automata with Application to Privacy-Preserving Virus Genome Detection

Hiroki Arimura, Jun Sakuma, Koji Tsuda, 2014, WPES.

Mis-operation Resistant Searchable Homomorphic Encryption

Jun Sakuma, Keita Emura, Noboru Kunihiro, 2017, AsiaCCS.

Attacking-Distance-Aware Attack: Semi-targeted Model Poisoning on Federated Learning

Yuwei Sun, H. Ochiai, Jun Sakuma, 2024, IEEE Transactions on Artificial Intelligence.