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FOCS
2000
IEEE
15 years 11 months ago
On Clusterings - Good, Bad and Spectral
We motivate and develop a natural bicriteria measure for assessing the quality of a clustering that avoids the drawbacks of existing measures. A simple recursive heuristic is shown...
Ravi Kannan, Santosh Vempala, Adrian Vetta
AADEBUG
1997
Springer
15 years 11 months ago
Application of Dynamic Slicing in Program Debugging
A dynamic program slice is an executable part of a program whose behavior is identical, for the same program input, to that of the original program with respect to a variable(s) o...
Bogdan Korel, Juergen Rilling
ICCV
1999
IEEE
16 years 8 months ago
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 7 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
EWSN
2004
Springer
16 years 6 months ago
Improving the Energy Efficiency of Directed Diffusion Using Passive Clustering
Directed diffusion is a prominent example of data-centric routing based on application layer data and purely local interactions. In its functioning it relies heavily on network-wid...
Andreas Köpke, Christian Frank, Holger Karl, ...