Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter
  Pruning   Conventional NAS-based pruning algorithms aim to find the sub-network with
the best validation performance. However, validation performance does not
successfully represent test performance, i.e., potential performance. Also,
although fine-tuning the pruned network to restore the performance drop is an
inevitable process, few studies have handled this issue. This paper proposes a
novel sub-network search and fine-tuning method that is named Ensemble
Knowledge Guidance (EKG). First, we experimentally prove that the fluctuation
of the loss landscape is an effective metric to evaluate the potential
performance. In order to search a sub-network with the smoothest loss landscape
at a low cost, we propose a pseudo-supernet built by an ensemble sub-network
knowledge distillation. Next, we propose a novel fine-tuning that re-uses the
information of the search phase. We store the interim sub-networks, that is,
the by-products of the search phase, and transfer their knowledge into the
pruned network. Note that EKG is easy to be plugged-in and computationally
efficient. For example, in the case of ResNet-50, about 45% of FLOPS is removed
without any performance drop in only 315 GPU hours. The implemented code is
available at https://github.com/sseung0703/EKG.

31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess