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» Machine-Learning Applications of Algorithmic Randomness
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104
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MLMI
2005
Springer
15 years 7 months ago
A Multimodal Discourse Ontology for Meeting Understanding
In this paper, we present a multimodal discourse ontology that serves as a knowledge representation and annotation framework for the discourse understanding component of an artifi...
John Niekrasz, Matthew Purver
CIVR
2003
Springer
133views Image Analysis» more  CIVR 2003»
15 years 6 months ago
A Closer Look at Boosted Image Retrieval
Margin-maximizing techniques such as boosting have been generating excitement in machine learning circles for several years now. Although these techniques offer significant impro...
Nicholas R. Howe
AAAI
2008
15 years 3 months ago
Instance-level Semisupervised Multiple Instance Learning
Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-...
Yangqing Jia, Changshui Zhang
132
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HIS
2008
15 years 3 months ago
REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
Hernán Ahumada, Guillermo L. Grinblat, Luca...
NIPS
2008
15 years 3 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas