Previous studies on multi-instance learning typically treated instances in the bags as
independently and identically distributed. The instances in a bag, however, are rarely independent …

Machine learning techniques have deeply rooted in our everyday life. However, since it is
knowledge- and labor-intensive to pursue good learning performance, human experts are …

In this paper, we propose the MIML (Multi-Instance Multi-Label learning) framework where
an example is described by multiple instances and associated with multiple class labels. …

While semi-supervised learning (SSL) has received tremendous attentions in many machine
learning tasks due to its successful use of unlabeled data, existing SSL algorithms use …

The global emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
pandemic can only be solved with effective and widespread preventive and …

It is usually expected that learning performance can be improved by exploiting unlabeled data,
particularly when the number of labeled data is limited. However, it has been reported that…

Both random Fourier features and the Nyström method have been successfully applied to
efficient kernel learning. In this work, we investigate the fundamental difference between these …

Cadmium (Cd) contamination in paddy fields is a serious health concern because of its high
toxicity and widespread pollution. Recently, much progress has been made in elucidating …

Determination of the neutrino mass hierarchy in a reactor neutrino experiment at the medium
baseline is discussed. Observation of the interference effects between the Δ m 31 2 and Δ …

Deep semi-supervised learning (SSL) has been recently shown very effectively. However,
its performance is seriously decreased when the class distribution is mismatched, among …