Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SPLASH: Learnable Activation Functions for Improving Accuracy and
  Adversarial Robustness   We introduce SPLASH units, a class of learnable activation functions shown to
simultaneously improve the accuracy of deep neural networks while also
improving their robustness to adversarial attacks. SPLASH units have both a
simple parameterization and maintain the ability to approximate a wide range of
non-linear functions. SPLASH units are: 1) continuous; 2) grounded (f(0) = 0);
3) use symmetric hinges; and 4) the locations of the hinges are derived
directly from the data (i.e. no learning required). Compared to nine other
learned and fixed activation functions, including ReLU and its variants, SPLASH
units show superior performance across three datasets (MNIST, CIFAR-10, and
CIFAR-100) and four architectures (LeNet5, All-CNN, ResNet-20, and
Network-in-Network). Furthermore, we show that SPLASH units significantly
increase the robustness of deep neural networks to adversarial attacks. Our
experiments on both black-box and open-box adversarial attacks show that
commonly-used architectures, namely LeNet5, All-CNN, ResNet-20, and
Network-in-Network, can be up to 31% more robust to adversarial attacks by
simply using SPLASH units instead of ReLUs.

21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex