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Grace Chu

5 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedCan weight sharing outperform random architecture search? An investigation with TuNAS

11 citations · 11 across the 1 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2020

Multi-path Neural Networks for On-device Multi-domain Visual Classification

Qifei Wang, Junjie Ke, Joshua Greaves +9

Learning multiple domains/tasks with a single model is important for improving data efficiency and lowering inference cost for numerous vision tasks, especially on resource-constra…

cs.CV2020

Discovering Multi-Hardware Mobile Models via Architecture Search

Grace Chu, Okan Arikan, Gabriel Bender +7

Hardware-aware neural architecture designs have been predominantly focusing on optimizing model performance on single hardware and model development complexity, where another impor…

cs.CV2019

Geo-Aware Networks for Fine-Grained Recognition

Grace Chu, Brian Potetz, Weijun Wang +5

Fine-grained recognition distinguishes among categories with subtle visual differences. In order to differentiate between these challenging visual categories, it is helpful to leve…

cs.CV2019

Searching for MobileNetV3

Andrew Howard, Mark Sandler, Grace Chu +9

We present the next generation of MobileNets based on a combination of complementary search techniques as well as a novel architecture design. MobileNetV3 is tuned to mobile phone…

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