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ICDM
2009
IEEE
92views Data Mining» more  ICDM 2009»
13 years 10 months ago
Semi-supervised Multi-task Learning with Task Regularizations
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
Fei Wang, Xin Wang, Tao Li
ICMLA
2010
13 years 10 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
ICML
2010
IEEE
14 years 1 months ago
Learning Programs: A Hierarchical Bayesian Approach
We are interested in learning programs for multiple related tasks given only a few training examples per task. Since the program for a single task is underdetermined by its data, ...
Percy Liang, Michael I. Jordan, Dan Klein
EMNLP
2008
14 years 1 months ago
Cross-Task Knowledge-Constrained Self Training
We present an algorithmic framework for learning multiple related tasks. Our framework exploits a form of prior knowledge that relates the output spaces of these tasks. We present...
Hal Daumé III
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
15 years 21 days ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
ICML
2009
IEEE
15 years 1 months ago
A convex formulation for learning shared structures from multiple tasks
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...
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye