A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
In order to reduce human efforts, there has been increasing interest in applying active learning for training text classifiers. This paper describes a straightforward active learni...
Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi W...
This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...