5 papers
X-DC: Explainable Deep Clustering based on Learnable Spectrogram Templates
Chihiro Watanabe, Hirokazu Kameoka
Deep neural networks (DNNs) have achieved substantial predictive performance in various speech processing tasks. Particularly, it has been shown that a monaural speech separation t…
Goodness-of-fit Test for Latent Block Models
Chihiro Watanabe, Taiji Suzuki
Latent block models are used for probabilistic biclustering, which is shown to be an effective method for analyzing various relational data sets. However, there has been no statist…
Interpreting Layered Neural Networks via Hierarchical Modular Representation
Chihiro Watanabe
Interpreting the prediction mechanism of complex models is currently one of the most important tasks in the machine learning field, especially with layered neural networks, which h…
Knowledge Discovery from Layered Neural Networks based on Non-negative Task Decomposition
Chihiro Watanabe, Kaoru Hiramatsu, Kunio Kashino
Interpretability has become an important issue in the machine learning field, along with the success of layered neural networks in various practical tasks. Since a trained layered…
Understanding Community Structure in Layered Neural Networks
Chihiro Watanabe, Kaoru Hiramatsu, Kunio Kashino
A layered neural network is now one of the most common choices for the prediction of high-dimensional practical data sets, where the relationship between input and output data is c…