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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 4 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
SODA
2010
ACM
261views Algorithms» more  SODA 2010»
16 years 1 months ago
Bidimensionality and Kernels
Bidimensionality theory appears to be a powerful framework in the development of meta-algorithmic techniques. It was introduced by Demaine et al. [J. ACM 2005 ] as a tool to obtai...
Fedor V. Fomin, Daniel Lokshtanov, Saket Saurabh, ...
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
16 years 1 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
IPSN
2009
Springer
15 years 10 months ago
Distributed resource management and matching in sensor networks
We consider a scenario in which there are resources at or near nodes of a network, which are either static (e.g. fire stations, parking spots) or mobile (e.g. police cars). Over ...
Jie Gao, Leonidas J. Guibas, Nikola Milosavljevic,...
FOCS
2009
IEEE
15 years 10 months ago
Planarity Allowing Few Error Vertices in Linear Time
— We show that for every fixed k, there is a linear time algorithm that decides whether or not a given graph has a vertex set X of order at most k such that G − X is planar (w...
Ken-ichi Kawarabayashi
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