118 search results - page 10 / 24 » Fast Algorithms for Constant Approximation k-Means Clusterin... |
CVPR
2005
IEEE
15 years 11 months ago
2005
IEEE
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
INFOCOM
2008
IEEE
15 years 3 months ago
2008
IEEE
—In a wireless network with node exclusive spectrum sharing, two popular schedules are maximum weight matching (MWM) schedule and maximum size matching (MSM) schedule. The former...
STACS
2007
Springer
15 years 3 months ago
2007
Springer
The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
100
Voted
ECCV
2010
Springer
15 years 2 months ago
2010
Springer
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
CVPR
2006
IEEE
15 years 11 months ago
2006
IEEE
In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...