Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-...
Coordinate gradient learning is motivated by the problem of variable selection and determining variable covariation. In this paper we propose a novel unifying framework for coordi...
This paperpresents several industrial applications of MLin the context of their effort to solve the "KAMLproblem", i.e., the problem of merging knowledge acquisition and...
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
The diversity of learning abilities between learners in the virtual classroom is wider than those in traditional classroom. It is difficult to prepare a suitable teaching material ...