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SODA
1998
ACM
113views Algorithms» more  SODA 1998»
15 years 8 months ago
Fast Hierarchical Clustering and Other Applications of Dynamic Closest Pairs
We develop data structures for dynamic closest pair problems with arbitrary (not necessarily geometric) distance functions, based on a technique previously used by the author for ...
David Eppstein
MCS
2008
Springer
15 years 7 months ago
Detecting multiple mean breaks at unknown points in official time series
In this paper, we propose a computationally effective approach to detect multiple structural breaks in the mean occurring at unknown dates. We present a non-parametric approach th...
Carmela Cappelli, Richard N. Penny, William S. Rea...
APIN
2000
87views more  APIN 2000»
15 years 6 months ago
The Architecture and Performance of a Stochastic Competitive Evolutionary Neural Tree Network
: A new dynamic tree structured network - the Stochastic Competitive Evolutionary Neural Tree (SCENT) is introduced. The network is able to provide a hierarchical classification of...
Neil Davey, Rod Adams, Stella J. George
CVPR
2012
IEEE
13 years 9 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
SCAM
2005
IEEE
16 years 19 days ago
Fine-Grained Analysis of Change Couplings
In software evolution analysis, many approaches analyze release history data available through versioning systems. The recent investigations of CVS data have shown that commonly c...
Beat Fluri, Harald Gall, Martin Pinzger