5046 search results - page 367 / 1010 » Non-redundant data clustering |
240
Voted
DAGSTUHL
2009
15 years 8 months ago
2009
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
192
Voted
ISBI
2008
IEEE
16 years 7 months ago
2008
IEEE
Most clustering algorithms in fMRI analysis implicitly require some nontrivial assumption on data structure. Due to arbitrary distribution of fMRI time series in the temporal doma...
204
click to vote
DAWAK
2006
Springer
15 years 10 months ago
2006
Springer
Abstract. Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view ...
213
Voted
PKDD
2000
Springer
15 years 10 months ago
2000
Springer
Abstract. A new constrained model is discussed as a way of incorporating efficiently a priori expert knowledge into a clustering problem of a given individual set. The first innova...
183
Voted
NIPS
2007
15 years 8 months ago
2007
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....