3 papers
cs.LG2023
Scalable Federated Learning for Clients with Different Input Image Sizes and Numbers of Output Categories
Shuhei Nitta, Taiji Suzuki, Albert Rodríguez Mulet +2
Federated learning is a privacy-preserving training method which consists of training from a plurality of clients but without sharing their confidential data. However, previous wor…
cs.LG2019
Decomposable-Net: Scalable Low-Rank Compression for Neural Networks
Atsushi Yaguchi, Taiji Suzuki, Shuhei Nitta +2
Compressing DNNs is important for the real-world applications operating on resource-constrained devices. However, we typically observe drastic performance deterioration when changi…
cs.LG2018
Adam Induces Implicit Weight Sparsity in Rectifier Neural Networks
Atsushi Yaguchi, Taiji Suzuki, Wataru Asano +3
In recent years, deep neural networks (DNNs) have been applied to various machine leaning tasks, including image recognition, speech recognition, and machine translation. However,…