Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adversarial Reciprocal Points Learning for Open Set Recognition   Open set recognition (OSR), aiming to simultaneously classify the seen
classes and identify the unseen classes as 'unknown', is essential for reliable
machine learning.The key challenge of OSR is how to reduce the empirical
classification risk on the labeled known data and the open space risk on the
potential unknown data simultaneously. To handle the challenge, we formulate
the open space risk problem from the perspective of multi-class integration,
and model the unexploited extra-class space with a novel concept Reciprocal
Point. Follow this, a novel learning framework, termed Adversarial Reciprocal
Point Learning (ARPL), is proposed to minimize the overlap of known
distribution and unknown distributions without loss of known classification
accuracy. Specifically, each reciprocal point is learned by the extra-class
space with the corresponding known category, and the confrontation among
multiple known categories are employed to reduce the empirical classification
risk. Then, an adversarial margin constraint is proposed to reduce the open
space risk by limiting the latent open space constructed by reciprocal points.
To further estimate the unknown distribution from open space, an instantiated
adversarial enhancement method is designed to generate diverse and confusing
training samples, based on the adversarial mechanism between the reciprocal
points and known classes. This can effectively enhance the model
distinguishability to the unknown classes. Extensive experimental results on
various benchmark datasets indicate that the proposed method is significantly
superior to other existing approaches and achieves state-of-the-art
performance.

26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th