Sciweavers

1164 search results - page 137 / 233
» A Model Selection Approach for Local Learning
Sort
View
ICML
2007
IEEE
15 years 11 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney

Book
778views
16 years 8 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
113
Voted
SIAMIS
2010
156views more  SIAMIS 2010»
14 years 4 months ago
Learning the Morphological Diversity
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
Gabriel Peyré, Jalal Fadili, Jean-Luc Starc...
CVPR
2008
IEEE
16 years 1 days ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
ICCV
2011
IEEE
13 years 10 months ago
Annotator Rationales for Visual Recognition
Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
Jeff Donahue, Kristen Grauman