Deep Learning Model Selection of Suboptimal Complexity

2018 ◽  
pp. 129-147
Author(s):  
Oleg Bakhteev ◽  
◽  
Vadim Strijov ◽  
Keyword(s):  
Deep Learning ◽  
Model Selection ◽  
Learning Model ◽  
Deep Learning Model ◽  
Selection Of

Deep Learning Model Selection of Suboptimal Complexity

2018 ◽  
Vol 79 (8) ◽  
pp. 1474-1488
Author(s):  
O. Yu. Bakhteev ◽  
V. V. Strijov
Keyword(s):  
Deep Learning ◽  
Model Selection ◽  
Learning Model ◽  
Deep Learning Model ◽  
Selection Of

Errata for "Cerebro: a data system for optimized deep learning model selection"

2021 ◽  
Vol 14 (6) ◽  
pp. 863-863
Author(s):  
Supun Nakandala ◽  
Yuhao Zhang ◽  
Arun Kumar
Keyword(s):  
Deep Learning ◽  
Model Selection ◽  
Learning Model ◽  
Communication Cost ◽  
Data System ◽  
Training Method ◽  
Fine Grained ◽  
Correct Communication ◽  
Deep Learning Model

We discovered that there was an inconsistency in the communication cost formulation for the decentralized fine-grained training method in Table 2 of our paper [1]. We used Horovod as the archetype for decentralized fine-grained approaches, and its correct communication cost is higher than what we had reported. So, we amend the communication cost of decentralized fine-grained to [EQUATION]

Deep Learning Model Selection Platform for Object Detection

2019 ◽  
Vol 8 (2) ◽  
pp. 66-73
Author(s):  
Hansol Lee ◽  
Younggwan Kim ◽  
Jiman Hong
Keyword(s):  
Deep Learning ◽  
Model Selection ◽  
Object Detection ◽  
Learning Model ◽  
Deep Learning Model

scholarly journals Adaptive deep learning model selection on embedded systems

2018 ◽  
Vol 53 (6) ◽  
pp. 31-43 ◽  
Author(s):  
Ben Taylor ◽  
Vicent Sanz Marco ◽  
Willy Wolff ◽  
Yehia Elkhatib ◽  
Zheng Wang
Keyword(s):  
Deep Learning ◽  
Model Selection ◽  
Embedded Systems ◽  
Learning Model ◽  
Deep Learning Model
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