26 citations · 48 across the 4 of their papers we have counts for
4 papers
MobileNetV4 -- Universal Models for the Mobile Ecosystem
Danfeng Qin, Chas Leichner, Manolis Delakis +11
We present the latest generation of MobileNets, known as MobileNetV4 (MNv4), featuring universally efficient architecture designs for mobile devices. At its core, we introduce the…
PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks
Marina Neseem, Conor McCullough, Randy Hsin +8
Low-precision quantization is recognized for its efficacy in neural network optimization. Our analysis reveals that non-quantized elementwise operations which are prevalent in laye…
Data-Free Neural Architecture Search via Recursive Label Calibration
Zechun Liu, Zhiqiang Shen, Yun Long +3
This paper aims to explore the feasibility of neural architecture search (NAS) given only a pre-trained model without using any original training data. This is an important circums…
Pareto-Optimal Quantized ResNet Is Mostly 4-bit
AmirAli Abdolrashidi, Lisa Wang, Shivani Agrawal +4
Quantization has become a popular technique to compress neural networks and reduce compute cost, but most prior work focuses on studying quantization without changing the network s…