Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SurReal: Fr\'echet Mean and Distance Transform for Complex-Valued Deep
  Learning   We develop a novel deep learning architecture for naturally complex-valued
data, which is often subject to complex scaling ambiguity. We treat each sample
as a field in the space of complex numbers. With the polar form of a
complex-valued number, the general group that acts in this space is the product
of planar rotation and non-zero scaling. This perspective allows us to develop
not only a novel convolution operator using weighted Fr\'echet mean (wFM) on a
Riemannian manifold, but also a novel fully connected layer operator using the
distance to the wFM, with natural equivariant properties to non-zero scaling
and planar rotation for the former and invariance properties for the latter.
  Compared to the baseline approach of learning real-valued neural network
models on the two-channel real-valued representation of complex-valued data,
our method achieves surreal performance on two publicly available
complex-valued datasets: MSTAR on SAR images and RadioML on radio frequency
signals. On MSTAR, at 8% of the baseline model size and with fewer than 45,000
parameters, our model improves the target classification accuracy from 94% to
98% on this highly imbalanced dataset. On RadioML, our model achieves
comparable RF modulation classification accuracy at 10% of the baseline model
size.

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The categories of this paper are: acc-phys
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: cond-mat
29
The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
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The categories of this paper are: math
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The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg