6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Data Augmentations in Deep Weight Spaces
Aviv Shamsian, David W. Zhang, Aviv Navon +10
Learning in weight spaces, where neural networks process the weights of other deep neural networks, has emerged as a promising research direction with applications in various field…
cs.LG2023★ 6 cited
Guided Deep Kernel Learning
Idan Achituve, Gal Chechik, Ethan Fetaya
Combining Gaussian processes with the expressive power of deep neural networks is commonly done nowadays through deep kernel learning (DKL). Unfortunately, due to the kernel optimi…
cs.NI2022★ 1 cited
Communication Efficient Distributed Learning over Wireless Channels
Idan Achituve, Wenbo Wang, Ethan Fetaya +1
Vertical distributed learning exploits the local features collected by multiple learning workers to form a better global model. However, the exchange of data between the workers an…