Nonparametric Bayesian Mixed-effects Models for Multi-task Learning.

Wang, Yuyang.
2017-04-24T15:11:49.757Z

Abstract: In many real world problems we are interested in learning multiple tasks while the training set for each task is quite small. When the different tasks are related, one can learn all tasks simultaneously and aim to get improved predictive performance by taking advantage of the common aspects of all tasks. This general idea is known as multi-task learning and it has been successfully inves... read more

Subjects
Tufts University. Department of Computer Science.
Permanent URL
http://hdl.handle.net/10427/012295
ID: tufts:22033
To Cite: DCA Citation Guide