no code implementations • 24 Oct 2020 • Masahiro Kato, Zhenghang Cui, Yoshihiro Fukuhara
In this paper, in order to acquire a more reliable classifier against adversarial attacks, we propose the method of Adversarial Training with a Rejection Option (ATRO).
no code implementations • 22 Oct 2020 • Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
The goal of classification with rejection is to avoid risky misclassification in error-critical applications such as medical diagnosis and product inspection.
1 code implementation • 3 Aug 2020 • Zhenghang Cui, Issei Sato
We then propose an efficient adaptive labeling algorithm using the proposed oracle and the positivity comparison oracle.
1 code implementation • 24 Jul 2019 • Zhenghang Cui, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
Although learning from triplet comparison data has been considered in many applications, an important fundamental question of whether we can learn a classifier only from triplet comparison data has remained unanswered.
no code implementations • ICLR 2019 • Hirono Okamoto, Shohei Ohsawa, Itto Higuchi, Haruka Murakami, Mizuki Sango, Zhenghang Cui, Masahiro Suzuki, Hiroshi Kajino, Yutaka Matsuo
It reformulates the posterior with a natural paring $\langle, \rangle: \mathcal{Z} \times \mathcal{Z}^* \rightarrow \Real$, which can be expanded to uncountable infinite domains such as continuous domains as well as interpolation.
no code implementations • 21 May 2018 • Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama
Another example is the Stein points (SP) method, which minimizes kernelized Stein discrepancy directly.
no code implementations • 1 May 2017 • Zhenghang Cui, Issei Sato, Masashi Sugiyama
As the emergence and the thriving development of social networks, a huge number of short texts are accumulated and need to be processed.