6 citations · 8 across the 3 of their papers we have counts for
3 papers
Breakdown Point of Robust Support Vector Machine
Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda
The support vector machine (SVM) is one of the most successful learning methods for solving classification problems. Despite its popularity, SVM has a serious drawback, that is sen…
A Unified Robust Classification Model
Akiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori
A wide variety of machine learning algorithms such as support vector machine (SVM), minimax probability machine (MPM), and Fisher discriminant analysis (FDA), exist for binary clas…
A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems
Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
In binary classification problems, mainly two approaches have been proposed; one is loss function approach and the other is uncertainty set approach. The loss function approach is…