122 search results - page 5 / 25 » Scalable and Interpretable Data Representation for High-Dime... |
NIPS
2007
14 years 12 months ago
2007
Maximum entropy analysis of binary variables provides an elegant way for studying the role of pairwise correlations in neural populations. Unfortunately, these approaches suffer f...
107
click to vote
CVPR
2007
IEEE
16 years 13 days ago
2007
IEEE
We present an algorithm, Hierarchical ISOmetric SelfOrganizing Map (H-ISOSOM), for a concise, organized manifold representation of complex, non-linear, large scale, high-dimension...
97
Voted
BMVC
2010
14 years 8 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
ACSC
2005
IEEE
15 years 4 months ago
2005
IEEE
The Self-Organizing Map (SOM) is one of the popular Artificial Neural Networks which is a useful in clustering and visualizing complex high dimensional data. Conventional SOMs are...
78
Voted
CORR
2011
Springer
14 years 5 months ago
2011
Springer
—While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI ...