Projects per year
In this paper we are concerned with multitask learning when task-specific features are available. We describe two ways of achieving this using Gaussian process predictors: in the first method, the data from all tasks is combined into one dataset, making use of the task-specific features. In the second method we train specific predictors for each reference task, and then combine their predictions using a gating network. We demonstrate these methods on a compiler performance prediction problem, where a task is defined as predicting the speed-up obtained when applying a sequence of code transformations to a given program.
|Title of host publication||Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS 2007)|
|Editors||Marina Meila, Xiaotong Shen|
|Publisher||Journal of Machine Learning Research: Workshop and Conference Proceedings|
|Number of pages||8|
|Publication status||Published - 2007|