Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Building architectures for autonomous rational behavior requires the integration of several AI components, such as planning, learning and execution monitoring. In most cases, the ...
We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data t...
Transfer learning aims at reusing the knowledge in some source tasks to improve the learning of a target task. Many transfer learning methods assume that the source tasks and the ...
Bin Cao, Sinno Jialin Pan, Yu Zhang, Dit-Yan Yeung...
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...