25 citations · 59 across the 15 of their papers we have counts for
4 papers · 1 filter
Convergences for Minimax Optimization Problems over Infinite-Dimensional Spaces Towards Stability in Adversarial Training
Takashi Furuya, Satoshi Okuda, Kazuma Suetake +1
Training neural networks that require adversarial optimization, such as generative adversarial networks (GANs) and unsupervised domain adaptations (UDAs), suffers from instability.…
Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks
Ryuji Saiin, Tomoya Shirakawa, Sota Yoshihara +2
In this article, we propose a new paradigm for training spiking neural networks (SNNs), spike accumulation forwarding (SAF). It is known that SNNs are energy-efficient but difficul…
Bayesian Generalization Error in Linear Neural Networks with Concept Bottleneck Structure and Multitask Formulation
Naoki Hayashi, Yoshihide Sawada
Concept bottleneck model (CBM) is a ubiquitous method that can interpret neural networks using concepts. In CBM, concepts are inserted between the output layer and the last interme…
Spiking Synaptic Penalty: Appropriate Penalty Term for Energy-Efficient Spiking Neural Networks
Kazuma Suetake, Takuya Ushimaru, Ryuji Saiin +1
Spiking neural networks (SNNs) are energy-efficient neural networks because of their spiking nature. However, as the spike firing rate of SNNs increases, the energy consumption doe…