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» Random Spanning Trees and the Prediction of Weighted Graphs
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PODC
2005
ACM
14 years 1 months ago
Proof labeling schemes
The problem of verifying a Minimum Spanning Tree (MST) was introduced by Tarjan in a sequential setting. Given a graph and a tree that spans it, the algorithm is required to check...
Amos Korman, Shay Kutten, David Peleg
CVPR
2011
IEEE
13 years 4 months ago
Nonparametric Density Estimation on A Graph: Learning Framework, Fast Approximation and Application in Image Segmentation
We present a novel framework for tree-structure embedded density estimation and its fast approximation for mode seeking. The proposed method could find diverse applications in co...
Zhiding Yu, Oscar Au, Ketan Tang
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 2 months ago
Evolutionary algorithms and matroid optimization problems
We analyze the performance of evolutionary algorithms on various matroid optimization problems that encompass a vast number of efficiently solvable as well as NP-hard combinatoria...
Joachim Reichel, Martin Skutella
ICML
2003
IEEE
14 years 8 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
COLT
2010
Springer
13 years 5 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...