29 citations · 58 across the 8 of their papers we have counts for
4 papers · 1 filter
Semi-supervised learning by selective training with pseudo labels via confidence estimation
Masato Ishii
We propose a novel semi-supervised learning (SSL) method that adopts selective training with pseudo labels. In our method, we generate hard pseudo-labels and also estimate their co…
Perspectives and Prospects on Transformer Architecture for Cross-Modal Tasks with Language and Vision
Andrew Shin, Masato Ishii, Takuya Narihira
Transformer architectures have brought about fundamental changes to computational linguistic field, which had been dominated by recurrent neural networks for many years. Its succes…
Neural Network Libraries: A Deep Learning Framework Designed from Engineers' Perspectives
Takuya Narihira, Javier Alonsogarcia, Fabien Cardinaux +14
While there exist a plethora of deep learning tools and frameworks, the fast-growing complexity of the field brings new demands and challenges, such as more flexible network design…
Source-free Domain Adaptation via Distributional Alignment by Matching Batch Normalization Statistics
Masato Ishii, Masashi Sugiyama
In this paper, we propose a novel domain adaptation method for the source-free setting. In this setting, we cannot access source data during adaptation, while unlabeled target data…