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» Semi-Supervised Multitask Learning
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2009
ACM
14 years 2 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
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 1 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»
13 years 7 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
14 years 2 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
14 years 28 days 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