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» Learning SVMs from Sloppily Labeled Data
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NIPS
2008
13 years 10 months ago
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
Daphna Weinshall, Hynek Hermansky, Alon Zweig, Jie...
CVPR
2010
IEEE
14 years 5 months ago
Nonparametric Higher-Order Learning for Interactive Segmentation
In this paper, we deal with a generative model for multi-label, interactive segmentation. To estimate the pixel likelihoods for each label, we propose a new higher-order formulatio...
Tae Hoon Kim (Seoul National University), Kyoung M...
NIPS
2001
13 years 10 months ago
Grammatical Bigrams
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Mark A. Paskin
CVPR
2006
IEEE
14 years 11 months ago
Graph Laplacian Kernels for Object Classification from a Single Example
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Hong Chang, Dit-Yan Yeung
WWW
2008
ACM
14 years 10 months ago
Automatically refining the wikipedia infobox ontology
The combined efforts of human volunteers have recently extracted numerous facts from Wikipedia, storing them as machine-harvestable object-attribute-value triples in Wikipedia inf...
Fei Wu, Daniel S. Weld