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» Constellations and the Unsupervised Learning of Graphs
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JMLR
2006
186views more  JMLR 2006»
13 years 7 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
CVPR
2010
IEEE
14 years 4 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
2008
13 years 9 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
CIKM
2010
Springer
13 years 5 months ago
Discovery of numerous specific topics via term co-occurrence analysis
We describe efficient techniques for construction of large term co-occurrence graphs, and investigate an application to the discovery of numerous fine-grained (specific) topics. A...
Omid Madani, Jiye Yu
MM
2010
ACM
151views Multimedia» more  MM 2010»
13 years 7 months ago
Explicit and implicit concept-based video retrieval with bipartite graph propagation model
The major scientific problem for content-based video retrieval is the semantic gap. Generally speaking, there are two appropriate ways to bridge the semantic gap: the first one is...
Lei Bao, Juan Cao, Yongdong Zhang, Jintao Li, Ming...