847 search results - page 70 / 170 » Approximation algorithms for projective clustering |
125
Voted
JMLR
2010
14 years 11 months ago
2010
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
122
click to vote
NIPS
2008
15 years 2 months ago
2008
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
109
Voted
ESANN
2008
15 years 2 months ago
2008
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
COLT
2008
Springer
15 years 2 months ago
2008
Springer
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
105
Voted
ATMOS
2007
15 years 2 months ago
2007
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...