2 papers
cs.LG2022
Federated Learning of Neural ODE Models with Different Iteration Counts
Yuto Hoshino, Hiroki Kawakami, Hiroki Matsutani
Federated learning is a distributed machine learning approach in which clients train models locally with their own data and upload them to a server so that their trained results ar…
cs.LG2021
A Low-Cost Neural ODE with Depthwise Separable Convolution for Edge Domain Adaptation on FPGAs
Hiroki Kawakami, Hirohisa Watanabe, Keisuke Sugiura +1
High-performance deep neural network (DNN)-based systems are in high demand in edge environments. Due to its high computational complexity, it is challenging to deploy DNNs on edge…