Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Input Invex Neural Network   In this paper, we present a novel method to constrain invexity on Neural
Networks (NN). Invex functions ensure every stationary point is global minima.
Hence, gradient descent commenced from any point will lead to the global
minima. Another advantage of invexity on NN is to divide data space locally
into two connected sets with a highly non-linear decision boundary by simply
thresholding the output. To this end, we formulate a universal invex function
approximator and employ it to enforce invexity in NN. We call it Input Invex
Neural Networks (II-NN). We first fit data with a known invex function,
followed by modification with a NN, compare the direction of the gradient and
penalize the direction of gradient on NN if it contradicts with the direction
of reference invex function. In order to penalize the direction of the gradient
we perform Gradient Clipped Gradient Penalty (GC-GP). We applied our method to
the existing NNs for both image classification and regression tasks. From the
extensive empirical and qualitative experiments, we observe that our method
gives the performance similar to ordinary NN yet having invexity. Our method
outperforms linear NN and Input Convex Neural Network (ICNN) with a large
margin. We publish our code and implementation details at github.

8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph