Consistent Nonparametric Different-Feature Selection via the Sparsest $k$-Subgraph Problem

no code implementations • 31 Jul 2017 • Satoshi Hara, Takayuki Katsuki, Hiroki Yanagisawa, Masaaki Imaizumi, Takafumi Ono, Ryo Okamoto, Shigeki Takeuchi

We show that the proposed method is computationally efficient and does not require any extra computation for model selection.

feature selection Model Selection

Anomaly detection in reconstructed quantum states using a machine-learning technique

no code implementations • 20 Jan 2014 • Satoshi Hara, Takafumi Ono, Ryo Okamoto, Takashi Washio, Shigeki Takeuchi

We demonstrate that the proposed method can more accurately detect small erroneous deviations in reconstructed density matrices, which contain intrinsic fluctuations due to the limited number of samples, than a naive method of checking the trace distance from the average of the given density matrices.

Anomaly Detection BIG-bench Machine Learning