Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
We propose a mediator architecture that allows a learning system to retrieve learning objects from heterogeneous repositories. A mediating component accepts queries formulated in a...
In this paper, we propose a novel formulation of the network clique detection problem by introducing a general network data representation framework. We show connections between o...
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guiba...
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
— The notion of affordances is often directly linked with studies on mirror and canonical neurons as well as studies that try to relate language. In our previous work, we had dev...