14 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.CV2023
Boosting Residual Networks with Group Knowledge
Shengji Tang, Peng Ye, Baopu Li +5
Recent research understands the residual networks from a new perspective of the implicit ensemble model. From this view, previous methods such as stochastic depth and stimulative t…
cs.LG2021★ 14 cited
Accelerating Sparse Deep Neural Networks
Asit Mishra, Jorge Albericio Latorre, Jeff Pool +5
As neural network model sizes have dramatically increased, so has the interest in various techniques to reduce their parameter counts and accelerate their execution. An active area…
cs.LG2020★ 4 cited
Self-Supervised GAN Compression
Chong Yu, Jeff Pool
Deep learning's success has led to larger and larger models to handle more and more complex tasks; trained models can contain millions of parameters. These large models are compute…