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Talaria: Interactively Optimizing Machine Learning Models for Efficient
  Inference

Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference

3 April 2024
Fred Hohman
Chaoqun Wang
Jinmook Lee
Jochen Görtler
Dominik Moritz
Jeffrey P. Bigham
Zhile Ren
Cecile Foret
Qi Shan
Xiaoyi Zhang
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Papers citing "Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference"

5 / 5 papers shown
Title
Compress and Compare: Interactively Evaluating Efficiency and Behavior
  Across ML Model Compression Experiments
Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments
Angie Boggust
Venkatesh Sivaraman
Yannick Assogba
Donghao Ren
Dominik Moritz
Fred Hohman
VLM
45
3
0
06 Aug 2024
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
136
679
0
31 Jan 2021
Benchmarking TinyML Systems: Challenges and Direction
Benchmarking TinyML Systems: Challenges and Direction
Colby R. Banbury
Vijay Janapa Reddi
Max Lam
William Fu
A. Fazel
...
Jae-sun Seo
Jeff Sieracki
Urmish Thakker
Marian Verhelst
Poonam Yadav
96
226
0
10 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,214
0
17 Apr 2017
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
229
74,467
0
18 May 2015
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