Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Activation Functions: A new paradigm for understanding Neural
  Networks   The scope of research in the domain of activation functions remains limited
and centered around improving the ease of optimization or generalization
quality of neural networks (NNs). However, to develop a deeper understanding of
deep learning, it becomes important to look at the non linear component of NNs
more carefully. In this paper, we aim to provide a generic form of activation
function along with appropriate mathematical grounding so as to allow for
insights into the working of NNs in future. We propose "Self-Learnable
Activation Functions" (SLAF), which are learned during training and are capable
of approximating most of the existing activation functions. SLAF is given as a
weighted sum of pre-defined basis elements which can serve for a good
approximation of the optimal activation function. The coefficients for these
basis elements allow a search in the entire space of continuous functions
(consisting of all the conventional activations). We propose various training
routines which can be used to achieve performance with SLAF equipped neural
networks (SLNNs). We prove that SLNNs can approximate any neural network with
lipschitz continuous activations, to any arbitrary error highlighting their
capacity and possible equivalence with standard NNs. Also, SLNNs can be
completely represented as a collections of finite degree polynomial upto the
very last layer obviating several hyper parameters like width and depth. Since
the optimization of SLNNs is still a challenge, we show that using SLAF along
with standard activations (like ReLU) can provide performance improvements with
only a small increase in number of parameters.

14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th