2 citations · 7 across the 6 of their papers we have counts for
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cs.LG2020
Density Fixing: Simple yet Effective Regularization Method based on the Class Prior
Masanari Kimura, Ryohei Izawa
Machine learning models suffer from overfitting, which is caused by a lack of labeled data. To tackle this problem, we proposed a framework of regularization methods, called densit…
cs.LG2019
New Perspective of Interpretability of Deep Neural Networks
Masanari Kimura, Masayuki Tanaka
Deep neural networks (DNNs) are known as black-box models. In other words, it is difficult to interpret the internal state of the model. Improving the interpretability of DNNs is o…
cs.LG2018
Node Centralities and Classification Performance for Characterizing Node Embedding Algorithms
Kento Nozawa, Masanari Kimura, Atsunori Kanemura
Embedding graph nodes into a vector space can allow the use of machine learning to e.g. predict node classes, but the study of node embedding algorithms is immature compared to the…