26 citations · 47 across the 2 of their papers we have counts for
3 papers
cs.LG2021★ 26 cited
How Do Adam and Training Strategies Help BNNs Optimization?
Zechun Liu, Zhiqiang Shen, Shichao Li +3
The best performing Binary Neural Networks (BNNs) are usually attained using Adam optimization and its multi-step training variants. However, to the best of our knowledge, few stud…
cs.LG2020★ 21 cited
Larq Compute Engine: Design, Benchmark, and Deploy State-of-the-Art Binarized Neural Networks
Tom Bannink, Arash Bakhtiari, Adam Hillier +5
We introduce Larq Compute Engine, the world's fastest Binarized Neural Network (BNN) inference engine, and use this framework to investigate several important questions about the e…
cs.LG2019
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization
Koen Helwegen, James Widdicombe, Lukas Geiger +3
Optimization of Binarized Neural Networks (BNNs) currently relies on real-valued latent weights to accumulate small update steps. In this paper, we argue that these latent weights…