In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously. In this paper, we consider the problem of learning shared s...
Automatic age estimation from facial images has aroused research interests in recent years due to its promising potential for some computer vision applications. Among the methods ...
Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
This paper reports on TaskTracer — a software system being designed to help highly multitasking knowledge workers rapidly locate, discover, and reuse past processes they used to...
Anton N. Dragunov, Thomas G. Dietterich, Kevin Joh...