Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Density Encoding Enables Resource-Efficient Randomly Connected Neural
  Networks   The deployment of machine learning algorithms on resource-constrained edge
devices is an important challenge from both theoretical and applied points of
view. In this article, we focus on resource-efficient randomly connected neural
networks known as Random Vector Functional Link (RVFL) networks since their
simple design and extremely fast training time make them very attractive for
solving many applied classification tasks. We propose to represent input
features via the density-based encoding known in the area of stochastic
computing and use the operations of binding and bundling from the area of
hyperdimensional computing for obtaining the activations of the hidden neurons.
Using a collection of 121 real-world datasets from the UCI Machine Learning
Repository, we empirically show that the proposed approach demonstrates higher
average accuracy than the conventional RVFL. We also demonstrate that it is
possible to represent the readout matrix using only integers in a limited range
with minimal loss in the accuracy. In this case, the proposed approach operates
only on small n-bits integers, which results in a computationally efficient
architecture. Finally, through hardware FPGA implementations, we show that such
an approach consumes approximately eleven times less energy than that of the
conventional RVFL.

17
The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph