5 search results - page 1 / 1 » Infinite Predictor Subspace Models for Multitask Learning |
JMLR
2010
13 years 17 days ago
2010
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
JMLR
2002
13 years 5 months ago
2002
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
TSP
2008
13 years 4 months ago
2008
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...