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AAAI
2010
13 years 10 months ago
Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories
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...
Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bi...
IUI
2005
ACM
14 years 3 months ago
TaskTracer: a desktop environment to support multi-tasking knowledge workers
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...
ICML
2008
IEEE
14 years 11 months ago
Multi-task compressive sensing with Dirichlet process priors
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
BIBM
2009
IEEE
192views Bioinformatics» more  BIBM 2009»
14 years 4 months ago
A Multi-task Feature Selection Filter for Microarray Classification
A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
Liang Lan, Slobodan Vucetic
JMLR
2008
88views more  JMLR 2008»
13 years 10 months ago
Universal Multi-Task Kernels
In this paper we are concerned with reproducing kernel Hilbert spaces HK of functions from an input space into a Hilbert space Y, an environment appropriate for multi-task learnin...
Andrea Caponnetto, Charles A. Micchelli, Massimili...