Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
Abstract. Dealing with heterogeneous ontologies by means of semantic mappings has become an important area of research and a number of systems for discovering mappings between onto...
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...
Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web’s natural language text. Knowledge-based weak supervision, using structured...
Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke S....