Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: NASOA: Towards Faster Task-oriented Online Fine-tuning with a Zoo of
  Models   Fine-tuning from pre-trained ImageNet models has been a simple, effective,
and popular approach for various computer vision tasks. The common practice of
fine-tuning is to adopt a default hyperparameter setting with a fixed
pre-trained model, while both of them are not optimized for specific tasks and
time constraints. Moreover, in cloud computing or GPU clusters where the tasks
arrive sequentially in a stream, faster online fine-tuning is a more desired
and realistic strategy for saving money, energy consumption, and CO2 emission.
In this paper, we propose a joint Neural Architecture Search and Online
Adaption framework named NASOA towards a faster task-oriented fine-tuning upon
the request of users. Specifically, NASOA first adopts an offline NAS to
identify a group of training-efficient networks to form a pretrained model zoo.
We propose a novel joint block and macro-level search space to enable a
flexible and efficient search. Then, by estimating fine-tuning performance via
an adaptive model by accumulating experience from the past tasks, an online
schedule generator is proposed to pick up the most suitable model and generate
a personalized training regime with respect to each desired task in a one-shot
fashion. The resulting model zoo is more training efficient than SOTA models,
e.g. 6x faster than RegNetY-16GF, and 1.7x faster than EfficientNetB3.
Experiments on multiple datasets also show that NASOA achieves much better
fine-tuning results, i.e. improving around 2.1% accuracy than the best
performance in RegNet series under various constraints and tasks; 40x faster
compared to the BOHB.

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The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
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The categories of this paper are: nlin
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The categories of this paper are: math-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
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The categories of this paper are: eess
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The categories of this paper are: econ
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The categories of this paper are: math
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The categories of this paper are: dg-ga
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The categories of this paper are: plasm-ph
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The categories of this paper are: q-alg
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The categories of this paper are: atom-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: chem-ph