101 citations · 177 across the 9 of their papers we have counts for
6 papers · 1 filter
BLOX: Macro Neural Architecture Search Benchmark and Algorithms
Thomas Chun Pong Chau, Łukasz Dudziak, Hongkai Wen +2
Neural architecture search (NAS) has been successfully used to design numerous high-performance neural networks. However, NAS is typically compute-intensive, so most existing appro…
Zero-Cost Operation Scoring in Differentiable Architecture Search
Lichuan Xiang, Łukasz Dudziak, Mohamed S. Abdelfattah +3
We formalize and analyze a fundamental component of differentiable neural architecture search (NAS): local "operation scoring" at each operation choice. We view existing operation…
Zero-Cost Proxies for Lightweight NAS
Mohamed S. Abdelfattah, Abhinav Mehrotra, Łukasz Dudziak +1
Neural Architecture Search (NAS) is quickly becoming the standard methodology to design neural network models. However, NAS is typically compute-intensive because multiple models n…
Iterative Compression of End-to-End ASR Model using AutoML
Abhinav Mehrotra, Łukasz Dudziak, Jinsu Yeo +9
Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques. Past research hav…
BRP-NAS: Prediction-based NAS using GCNs
Łukasz Dudziak, Thomas Chau, Mohamed S. Abdelfattah +3
Neural architecture search (NAS) enables researchers to automatically explore broad design spaces in order to improve efficiency of neural networks. This efficiency is especially i…
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning
Łukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla +2
End-to-end automatic speech recognition (ASR) models are increasingly large and complex to achieve the best possible accuracy. In this paper, we build an AutoML system that uses re…