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» A Scheme for Approximating Probabilistic Inference
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ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 8 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
ICIP
2002
IEEE
14 years 10 months ago
A Bayesian approach to inferring vascular tree structure from 2D imagery
We describe a method for inferring tree-like vascular structures from 2D imagery. A Markov Chain Monte Carlo (MCMC) algorithm is employed to produce approximate samples from the p...
Abhir Bhalerao, Elke Thönnes, Roland Wilson, ...
ICML
2005
IEEE
14 years 9 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
SIGMETRICS
2010
ACM
203views Hardware» more  SIGMETRICS 2010»
13 years 9 months ago
An analytical framework to infer multihop path reliability in MANETs
Abstract Due to complexity and intractability reasons, most of the analytical studies on the reliability of communication paths in mobile ad hoc networks are based on the assumptio...
Nelson Antunes, Gonçalo Jacinto, Antó...
ICCV
2001
IEEE
14 years 10 months ago
Continuous Global Evidence-Based Bayesian Modality Fusion for Simultaneous Tracking of Multiple Objects
Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
Jamie Sherrah, Shaogang Gong