2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Cuttlefish: Low-Rank Model Training without All the Tuning
Hongyi Wang, Saurabh Agarwal, Pongsakorn U-chupala +3
Recent research has shown that training low-rank neural networks can effectively reduce the total number of trainable parameters without sacrificing predictive accuracy, resulting…
cs.CV2022★ 2 cited
MRL: Learning to Mix with Attention and Convolutions
Shlok Mohta, Hisahiro Suganuma, Yoshiki Tanaka
In this paper, we present a new neural architectural block for the vision domain, named Mixing Regionally and Locally (MRL), developed with the aim of effectively and efficiently m…