Tetsuya Sakurai

A Training Difficulty Schedule for Effective Search of Meta-Heuristic Design

2020

In the context of optimization problems, the performance of an algorithm depends on the problem. It is difficult to know a priori what algorithm (and what parameters) will perform best on a new problem. For …

LSEC: Large-scale spectral ensemble clustering

2021 · arXiv (Cornell University)

Ensemble clustering is a fundamental problem in the machine learning field, combining multiple base clusterings into a better clustering result. However, most of the existing methods are unsuitable for large-scale ensemble clustering tasks due to …

A study of the privacy perspective on principal component analysis via a realistic attack model

2022

Anonymization methods based on principal component analysis (PCA), one of dimensionality reduction methods, have been well studied. These combine PCA with noise addition. Some of these methods theoretically guarantee privacy but decrease utility because of …