20 citations · 51 across the 11 of their papers we have counts for
3 papers · 1 filter
Few-shot Learning for Unsupervised Feature Selection
Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
We propose a few-shot learning method for unsupervised feature selection, which is a task to select a subset of relevant features in unlabeled data. Existing methods usually requir…
Network Implosion: Effective Model Compression for ResNets via Static Layer Pruning and Retraining
Yasutoshi Ida, Yasuhiro Fujiwara
Residual Networks with convolutional layers are widely used in the field of machine learning. Since they effectively extract features from input data by stacking multiple layers, t…
Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks
Yasutoshi Ida, Yasuhiro Fujiwara, Sotetsu Iwamura
Adaptive learning rate algorithms such as RMSProp are widely used for training deep neural networks. RMSProp offers efficient training since it uses first order gradients to approx…