65 search results - page 6 / 13 » Is Nonparametric Learning Practical in Very High Dimensional... |
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
NIPS
1996
13 years 8 months ago
1996
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
SAC
2006
ACM
14 years 1 months ago
2006
ACM
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
JEA
2008
13 years 7 months ago
2008
The Spatial Approximation Tree (sa-tree) is a recently proposed data structure for searching in metric spaces. It has been shown that it compares favorably against alternative data...
IJCAI
2007
13 years 9 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...