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» Algorithmic randomness of continuous functions
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CORR
2010
Springer
134views Education» more  CORR 2010»
14 years 10 months ago
Incremental Sampling-based Algorithms for Optimal Motion Planning
During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to po...
Sertac Karaman, Emilio Frazzoli
CVPR
2009
IEEE
16 years 4 months ago
Global Connectivity Potentials for Random Field Models
Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions a...
Sebastian Nowozin, Christoph H. Lampert
ICCV
2009
IEEE
16 years 2 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
15 years 3 months ago
Genetic algorithms using low-discrepancy sequences
The random number generator is one of the important components of evolutionary algorithms (EAs). Therefore, when we try to solve function optimization problems using EAs, we must ...
Shuhei Kimura, Koki Matsumura
WAW
2009
Springer
150views Algorithms» more  WAW 2009»
15 years 4 months ago
The Giant Component in a Random Subgraph of a Given Graph
We consider a random subgraph Gp of a host graph G formed by retaining each edge of G with probability p. We address the question of determining the critical value p (as a function...
Fan Chung Graham, Paul Horn, Linyuan Lu