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» Semi-Supervised Multitask Learning
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2009
ACM
15 years 6 months ago
Lessons learned from a year's worth of benchmarks of large data clouds
In this paper, we discuss some of the lessons that we have learned working with the Hadoop and Sector/Sphere systems. Both of these systems are cloud-based systems designed to sup...
Yunhong Gu, Robert L. Grossman
80
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GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 5 months ago
Genetic programming for cross-task knowledge sharing
We consider multitask learning of visual concepts within genetic programming (GP) framework. The proposed method evolves a population of GP individuals, with each of them composed...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...
CORR
2008
Springer
99views Education» more  CORR 2008»
14 years 11 months ago
When is there a representer theorem? Vector versus matrix regularizers
We consider a general class of regularization methods which learn a vector of parameters on the basis of linear measurements. It is well known that if the regularizer is a nondecr...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
ICTIR
2009
Springer
15 years 5 months ago
Robust Word Similarity Estimation Using Perturbation Kernels
We introduce perturbation kernels, a new class of similarity measure for information retrieval that casts word similarity in terms of multi-task learning. Perturbation kernels mode...
Kevyn Collins-Thompson
ICDAR
2003
IEEE
15 years 4 months ago
Character Recognition by Adaptive Statistical Similarity
Handwriting recognition and OCR systems need to cope with a wide variety of writing styles and fonts, many of them possibly not previously encountered during training. This paper d...
Thomas M. Breuel