Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Interspace Pruning: Using Adaptive Filter Representations to Improve
  Training of Sparse CNNs   Unstructured pruning is well suited to reduce the memory footprint of
convolutional neural networks (CNNs), both at training and inference time. CNNs
contain parameters arranged in $K \times K$ filters. Standard unstructured
pruning (SP) reduces the memory footprint of CNNs by setting filter elements to
zero, thereby specifying a fixed subspace that constrains the filter.
Especially if pruning is applied before or during training, this induces a
strong bias. To overcome this, we introduce interspace pruning (IP), a general
tool to improve existing pruning methods. It uses filters represented in a
dynamic interspace by linear combinations of an underlying adaptive filter
basis (FB). For IP, FB coefficients are set to zero while un-pruned
coefficients and FBs are trained jointly. In this work, we provide mathematical
evidence for IP's superior performance and demonstrate that IP outperforms SP
on all tested state-of-the-art unstructured pruning methods. Especially in
challenging situations, like pruning for ImageNet or pruning to high sparsity,
IP greatly exceeds SP with equal runtime and parameter costs. Finally, we show
that advances of IP are due to improved trainability and superior
generalization ability.

18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess