137 search results - page 8 / 28 » Ordinal Embedding: Approximation Algorithms and Dimensionali... |
ICIC
2009
Springer
14 years 10 days ago
2009
Springer
Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant...
ICML
2004
IEEE
14 years 1 months ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
PAKDD
2010
ACM
13 years 5 months ago
2010
ACM
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
AAAI
2010
13 years 9 months ago
2010
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
PAMI
2006
13 years 7 months ago
2006
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...