Transfer learning borrows knowledge from a source domain to facilitate learning in a target domain. Two primary issues to be addressed in transfer learning are what and how to transfer. For a pair of domains, adopting different transfer learning algorithms results in different knowledge transferred between them. To discover the optimal transfer learning algorithm that maximally improves the lea...

Human learners appear to have inherent ways to transfer knowledge between tasks. That is, we recognize and apply relevant knowledge from previous learning experiences when we encounter new tasks. The more related a new task is to our previous experience, the more easily we can master it. Common machine learning algorithms, in contrast, traditionally address isolated tasks. Transfer learning att...

the purpose of this study is to extend the existing knowledge of inter-firm knowledge transfer research and provide a deeper understanding of knowledge transfer practice in an alliance context, as well as the reasons for such a practice. this study reports on relevant results derived from semi-structured interviews with 16 top managers in a chinese international joint venture (ijv) formed by tw...

this study was conducted to compare the impact of two vocabulary learning techniques, namely context learning and translation learning, on vocabulary recall of sixty pre-university iranian learners of english as a foreign language. they were divided into two groups of high and low proficient. in regard to two vocabulary learning conditions, each group was divided into two subgroups of fifteen. ...

In sentiment classification, unlabeled user reviews are often free to collect for new products, while sentiment labels are rare. In this case, active learning is often applied to build a high-quality classifier with as small amount of labeled instances as possible. However, when the labeled instances are insufficient, the performance of active learning is limited. In this paper, we aim at enhan...

Transfer learning can be described as the distillation of abstract knowledge from one learning domain or task and the reuse of that knowledge in a related domain or task. In categorization settings, transfer learning is the modification by past experience of prior expectations about what types of categories are likely to exist in the world. While transfer learning is an important and active res...

The current experiment investigated generalizability of motor learning in proximal versus distal effectors in upper extremities. Twenty-eight participants were divided into three groups: training proximal effectors, training distal effectors, and no training control group (CG). Performance was tested pre- and post-training for specific learning and three learning transfer conditions: (1) bilate...