In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...
Fatigue has been implicated in an alarming number of motor vehicle accidents, costing billions of dollars and thousands of lives. Unfortunately, the ability to predict performance...
Glenn Gunzelmann, L. Richard Moore, Dario D. Salvu...
In the past, a priori interconnect prediction, based on Rent’s rule, has been applied mainly for technology evaluation and roadmap applications. These applications do not requir...
Power transformers' failures carry great costs to electric companies since they need resources to recover from them and to perform periodical maintenance. To avoid this probl...
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...