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» Learning from Multiple Sources of Inaccurate Data
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CVPR
2009
IEEE
16 years 10 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
129
Voted
MICCAI
2005
Springer
16 years 4 months ago
Multiscale 3D Shape Analysis Using Spherical Wavelets
Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of vari...
Delphine Nain, Steven Haker, Aaron F. Bobick, Alle...
SIGMETRICS
2009
ACM
157views Hardware» more  SIGMETRICS 2009»
15 years 10 months ago
Delay tolerant bulk data transfers on the internet
Many emerging scientific and industrial applications require transferring multiple Tbytes of data on a daily basis. Examples include pushing scientific data from particle accele...
Nikolaos Laoutaris, Georgios Smaragdakis, Pablo Ro...
135
Voted
BMCBI
2008
121views more  BMCBI 2008»
15 years 3 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...
PAMI
2008
196views more  PAMI 2008»
15 years 3 months ago
Distance Learning for Similarity Estimation
In this paper, we present a general guideline to find a better distance measure for similarity estimation based on statistical analysis of distribution models and distance function...
Jie Yu, Jaume Amores, Nicu Sebe, Petia Radeva, Qi ...