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JCSS
2008
138views more  JCSS 2008»
15 years 6 months ago
Reducing mechanism design to algorithm design via machine learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
JMLR
2011
157views more  JMLR 2011»
15 years 1 months ago
Variable Sparsity Kernel Learning
This paper1 presents novel algorithms and applications for a particular class of mixed-norm regularization based Multiple Kernel Learning (MKL) formulations. The formulations assu...
Jonathan Aflalo, Aharon Ben-Tal, Chiranjib Bhattac...
CVPR
2004
IEEE
16 years 8 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
CVPR
2008
IEEE
16 years 8 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell
WWW
2002
ACM
16 years 7 months ago
Learning to map between ontologies on the semantic web
Ontologies play a prominent role on the Semantic Web. They make possible the widespread publication of machine understandable data, opening myriad opportunities for automated info...
AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon ...