879 search results - page 105 / 176 » Forecasting high-dimensional data |
NIPS
2007
14 years 11 months ago
2007
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
DATAMINE
2007
14 years 9 months ago
2007
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
110
click to vote
SSPR
2010
Springer
14 years 8 months ago
2010
Springer
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
114
click to vote
MMM
2011
Springer
14 years 1 months ago
2011
Springer
Abstract. Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree...
TGIS
2002
14 years 9 months ago
2002
The research field of transportation demand forecasting has started to focus on disaggregate travel behavior and micro-simulation models. To create data infrastructure, disaggrega...