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ECML
2005
Springer
14 years 2 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu
PR
2010
158views more  PR 2010»
13 years 7 months ago
Out-of-bag estimation of the optimal sample size in bagging
The performance of m-out-of-n bagging with and without replacement in terms of the sampling ratio (m/n) is analyzed. Standard bagging uses resampling with replacement to generate ...
Gonzalo Martínez-Muñoz, Alberto Su&a...
BMCBI
2004
141views more  BMCBI 2004»
13 years 8 months ago
Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
Background: Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistical...
Ruslan Sadreyev, Nick V. Grishin
TIP
2010
123views more  TIP 2010»
13 years 7 months ago
Optimizing Motion Compensated Prediction for Error Resilient Video Coding
—This paper is concerned with optimization of the motion compensated prediction framework to improve the error resilience of video coding for transmission over lossy networks. Fi...
Hua Yang, Kenneth Rose
ICRA
2000
IEEE
96views Robotics» more  ICRA 2000»
14 years 29 days ago
Fault Detection for Robot Manipulators with Parametric Uncertainty: A Prediction Error Based Approach
—In this paper, we introduce a new approach to fault detection for robot manipulators. The technique, which is based on the isolation of fault signatures via filtered torque pred...
Warren E. Dixon, Ian D. Walker, Darren M. Dawson, ...