Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Multi-view learning has become a hot topic during the past few years. In this paper, we first characterize the sample complexity of multi-view active learning. Under the expansion...