Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
— In this work, we perform an extensive statistical evaluation for learning and recognition of object manipulation actions. We concentrate on single arm/hand actions but study th...
This paper proposes a model-driven, extensible platform, delivered on the Web, which is able to support long-distance collaboration of students’ teams working on complex projects...
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
This paper proposes extending semi-supervised learning by allowing an ongoing interaction between a user and the system. The extension is intended to not only to speed up search fo...