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» A Graph Pebbling Algorithm on Weighted Graphs
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ICML
2003
IEEE
14 years 9 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
SODA
2008
ACM
93views Algorithms» more  SODA 2008»
13 years 10 months ago
Minimum weight convex Steiner partitions
New tight bounds are presented on the minimum length of planar straight line graphs connecting n given points in the plane and having convex faces. Specifically, we show that the ...
Adrian Dumitrescu, Csaba D. Tóth
VDA
2010
247views Visualization» more  VDA 2010»
13 years 11 months ago
Flow Web: a graph based user interface for 3D flow field exploration
While there have been intensive efforts in developing better 3D flow visualization techniques, little attention has been paid to the design of better user interfaces and more effe...
Lijie Xu, Han-Wei Shen
ICGA
1993
296views Optimization» more  ICGA 1993»
13 years 10 months ago
A Genetic Algorithm Applied to the Maximum Flow Problem
A genetic algorithms is applied to find a maximum flow from the source to sink in a weighted directed graph, where the weight associated with each edge represents its flow capacit...
Toshinori Munakata, David J. Hashier
CORR
2010
Springer
94views Education» more  CORR 2010»
13 years 7 months ago
When LP is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings
Abstract Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy match...
Nikhil Bansal, Anupam Gupta, Jian Li, Juliá...