1 citations · 2 across the 20 of their papers we have counts for
4 papers · 1 filter
Bounding the Worst-class Error: A Boosting Approach
Yuya Saito, Shinnosuke Matsuo, Seiichi Uchida +1
This paper tackles the problem of the worst-class error rate, instead of the standard error rate averaged over all classes. For example, a three-class classification task with clas…
Deep Attentive Time Warping
Shinnosuke Matsuo, Xiaomeng Wu, Gantugs Atarsaikhan +4
Similarity measures for time series are important problems for time series classification. To handle the nonlinear time distortions, Dynamic Time Warping (DTW) has been widely used…
MixBag: Bag-Level Data Augmentation for Learning from Label Proportions
Takanori Asanomi, Shinnosuke Matsuo, Daiki Suehiro +1
Learning from label proportions (LLP) is a promising weakly supervised learning problem. In LLP, a set of instances (bag) has label proportions, but no instance-level labels are gi…
Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimization
Shinnosuke Matsuo, Ryoma Bise, Seiichi Uchida +1
This paper proposes a novel and efficient method for Learning from Label Proportions (LLP), whose goal is to train a classifier only by using the class label proportions of instanc…