2512 search results - page 353 / 503 » Learning from Highly Structured Data by Decomposition |
150
Voted
CVPR
2007
IEEE
16 years 6 months ago
2007
IEEE
We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
122
Voted
SMC
2007
IEEE
15 years 10 months ago
2007
IEEE
— The basic objective of this work is to assess the utility of two supervised learning algorithms AdaBoost and RIPPER for classifying SSH traffic from log files without using f...
133
Voted
NN
2006
Springer
15 years 3 months ago
2006
Springer
Previous studies have shown that non-human primates can generate highly stochastic choice behaviour, especially when this is required during a competitive interaction with another...
118
Voted
NIPS
1998
15 years 5 months ago
1998
A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, ho...
241
Voted
EGPGV
2011
Springer
14 years 7 months ago
2011
Springer
We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...