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JMLR
2010
136views more  JMLR 2010»
14 years 9 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
SEKE
2007
Springer
15 years 8 months ago
Adjudicator: A Statistical Approach for Learning Ontology Concepts from Peer Agents
— We present a statistical approach for software agents to learn ontology concepts from peer agents by asking them whether they can reach consensus on significant differences bet...
Behrouz Homayoun Far, Abdel Halim Elamy, Nora Houa...
AAAI
2010
15 years 3 months ago
Facial Age Estimation by Learning from Label Distributions
One of the main difficulties in facial age estimation is the lack of sufficient training data for many ages. Fortunately, the faces at close ages look similar since aging is a slo...
Xin Geng, Kate Smith-Miles, Zhi-Hua Zhou
MICCAI
2007
Springer
15 years 8 months ago
Robust Autonomous Model Learning from 2D and 3D Data Sets
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
ICML
2003
IEEE
16 years 3 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker