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JACM
2006
99views more  JACM 2006»
13 years 7 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
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 8 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
STOC
2010
ACM
261views Algorithms» more  STOC 2010»
14 years 12 days ago
An Improved LP-based Approximation for Steiner Tree
The Steiner tree problem is one of the most fundamental ÆÈ-hard problems: given a weighted undirected graph and a subset of terminal nodes, find a minimum weight tree spanning ...
Jaroslaw Byrka, Fabrizio Grandoni, Thomas Rothvoss...
ICPR
2010
IEEE
14 years 2 months ago
Integrating a Discrete Motion Model into GMM Based Background Subtraction
GMM based algorithms have become the de facto standard for background subtraction in video sequences, mainly because of their ability to track multiple background distributions, w...
Christian Wolf, Jolion Jolion
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 8 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor