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JACM
2006
99views more  JACM 2006»
15 years 6 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller
SDM
2009
SIAM
343views Data Mining» more  SDM 2009»
16 years 4 months ago
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been acti...
Masashi Sugiyama, Yoshinobu Kawahara
EVOW
2009
Springer
16 years 1 months ago
Improving Performance in Combinatorial Optimisation Using Averaging and Clustering
In a recent paper an algorithm for solving MAX-SAT was proposed which worked by clustering good solutions and restarting the search from the closest feasible solutions. This was sh...
Mohamed Qasem, Adam Prügel-Bennett
ICPR
2008
IEEE
16 years 1 months ago
Detecting hubs and quasi cliques in scale-free networks
Scale-free networks are believed to closely model most real-world networks. An interesting property of such networks is the existence of so-called hub and community structures. In...
Sriganesh Srihari, Hoong Kee Ng, Kang Ning, Hon Wa...
CSCLP
2007
Springer
16 years 1 months ago
Temporal Reasoning in Nested Temporal Networks with Alternatives
Temporal networks play a crucial role in modeling temporal relations in planning and scheduling applications. Temporal Networks with Alternatives (TNAs) were proposed to model alte...
Roman Barták, Ondrej Cepek, Martin Hejna