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ML
2006
ACM
163views Machine Learning» more  ML 2006»
15 years 5 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
ICIP
2010
IEEE
15 years 3 months ago
Randomized motion estimation
Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast mo...
Sylvain Boltz, Frank Nielsen
ICALP
2009
Springer
16 years 5 months ago
Revisiting the Direct Sum Theorem and Space Lower Bounds in Random Order Streams
Estimating frequency moments and Lp distances are well studied problems in the adversarial data stream model and tight space bounds are known for these two problems. There has been...
Sudipto Guha, Zhiyi Huang
CEC
2005
IEEE
15 years 11 months ago
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm
Abstract- Markov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)...
Siddhartha Shakya, John A. W. McCall, Deryck F. Br...
ECCV
2010
Springer
15 years 10 months ago
Reweighted Random Walks for Graph Matching
Graph matching is an essential problem in computer vision and machine learning. In this paper, we introduce a random walk view on the problem and propose a robust graph matching al...
Minsu Cho (Seoul National University), Jungmin Lee...