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» Learning Functions from Imperfect Positive Data
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CIARP
2006
Springer
15 years 8 months ago
Robustness Analysis of the Neural Gas Learning Algorithm
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
Carolina Saavedra, Sebastián Moreno, Rodrig...
MLDM
2009
Springer
16 years 1 months ago
Dynamic Score Combination: A Supervised and Unsupervised Score Combination Method
In two-class score-based problems the combination of scores from an ensemble of experts is generally used to obtain distributions for positive and negative patterns that exhibit a ...
Roberto Tronci, Giorgio Giacinto, Fabio Roli
ICRA
2002
IEEE
104views Robotics» more  ICRA 2002»
15 years 11 months ago
A Visual Landmark Framework for Indoor Mobile Robot Navigation
This article presents vision functions needed on a mobile robot to deal with landmark-based navigation in buildings. Landmarks are planar, quadrangular surfaces, which must be dis...
Jean-Bernard Hayet, Frédéric Lerasle...
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
15 years 4 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim
AAAI
2010
15 years 8 months ago
A Layered Approach to People Detection in 3D Range Data
People tracking is a key technology for autonomous systems, intelligent cars and social robots operating in populated environments. What makes the task difficult is that the appea...
Luciano Spinello, Kai Oliver Arras, Rudolph Triebe...