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ICML
2005
IEEE
14 years 8 months ago
Predicting relative performance of classifiers from samples
This paper is concerned with the problem of predicting relative performance of classification algorithms. It focusses on methods that use results on small samples and discusses th...
Rui Leite, Pavel Brazdil
AAAI
2004
13 years 9 months ago
Towards Efficient Sampling: Exploiting Random Walk Strategies
From a computational perspective, there is a close connection between various probabilistic reasoning tasks and the problem of counting or sampling satisfying assignments of a pro...
Wei Wei, Jordan Erenrich, Bart Selman
EVOW
2005
Springer
14 years 1 months ago
Granular Sampling Using a Pulse-Coupled Network of Spiking Neurons
Abstract. We present a new technique for granular sampling using a pulsecoupled network of spiking artificial neurons to generate grain events. The system plays randomly selected s...
Eduardo Reck Miranda, John Matthias
ALGOSENSORS
2008
Springer
13 years 9 months ago
Algorithms for Location Estimation Based on RSSI Sampling
In this paper, we re-examine the RSSI measurement model for location estimation and provide the first detailed formulation of the probability distribution of the position of a sens...
Charalampos Papamanthou, Franco P. Preparata, Robe...
ICCV
2009
IEEE
13 years 5 months ago
Exploiting uncertainty in random sample consensus
In this work, we present a technique for robust estimation, which by explicitly incorporating the inherent uncertainty of the estimation procedure, results in a more efficient rob...
Rahul Raguram, Jan-Michael Frahm, Marc Pollefeys