We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advant...
We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that l...
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...