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104
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AAAI
2010
15 years 19 days 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...
92
Voted
IUI
2005
ACM
15 years 6 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...
99
Voted
ICML
2008
IEEE
16 years 1 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»
15 years 7 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
102
Voted
JMLR
2008
88views more  JMLR 2008»
15 years 12 days 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...