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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 3 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 29 days 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 21 days 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