Jun Sakuma

Recommendation with k-anonymized Ratings

2017 · arXiv (Cornell University)

Recommender systems are widely used to predict personalized preferences of goods or services using users' past activities, such as item ratings or purchase histories. If collections of such personal activities were made publicly available, they …

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

2018

An efficient secure two-party computation protocol of matrix multiplication allows privacy-preserving cloud-aid machine learning services such as face recognition and traffic-aware navigation. We use homomorphic encryption to construct a secure matrix multiplication protocol with a …

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

2021 · Proceedings of the Genetic and Evolutionary Computation Conference

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, applications of existing ML-based level generations are mostly limited to …

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

2022 · 2022 International Joint Conference on Neural Networks (IJCNN)

Model poisoning attacks on federated learning intrude in the entire system via compromising an edge model, resulting in malfunctioning of machine learning models. Such compromised models are tampered with to perform adversary-desired behaviors. In particular, …