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ICML
1994
IEEE
13 years 11 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee
ECML
2005
Springer
14 years 1 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
ICML
2001
IEEE
14 years 8 months ago
Bayesian approaches to failure prediction for disk drives
Hard disk drive failures are rare but are often costly. The ability to predict failures is important to consumers, drive manufacturers, and computer system manufacturers alike. In...
Greg Hamerly, Charles Elkan
ICASSP
2009
IEEE
14 years 2 months ago
On the use of Bayesian modeling for predicting noise reduction performance
In speech enhancement applications, a validated metric of noise reduction performance is vital in the relative ranking of noise reduction algorithms and in enhancing the performan...
Nazanin Pourmand, David Suelzle, Vijay Parsa, Yi H...
WAA
2001
Springer
13 years 12 months ago
Wavelet-Based Video Compression Using Long-Term Memory Motion-Compensated Prediction and Context-Based Adaptive Arithmetic Codin
In this paper, we present a novel design of a wavelet-based video coding algorithm within a conventional hybrid framework of temporal motion-compensated prediction and transform co...
Detlev Marpe, Thomas Wiegand, Hans L. Cycon