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» On learning with dissimilarity functions
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FGR
2000
IEEE
112views Biometrics» more  FGR 2000»
15 years 11 months ago
Viewpoint-Invariant Learning and Detection of Human Heads
We present a method to learn models of human heads for the purpose of detection from different viewing angles. We focus on a model where objects are represented as constellations ...
Markus Weber, Wolfgang Einhäuser, Max Welling...
GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
15 years 10 months ago
A Bayesian approach to learning classifier systems in uncertain environments
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...
KDD
1995
ACM
112views Data Mining» more  KDD 1995»
15 years 10 months ago
Learning First Order Logic Rules with a Genetic Algorithm
This paper introduces a newalgorithm called SIAO1 for learning first order logic rules withgenetic algorithms. SIAO1uses the covering principle developed in AQwhereseed examplesar...
Sébastien Augier, Gilles Venturini, Yves Ko...
WSC
2008
15 years 9 months ago
On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
Abhijit Gosavi
EMNLP
2008
15 years 8 months ago
Learning with Probabilistic Features for Improved Pipeline Models
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Razvan C. Bunescu