Bayesian methods for Support Vector machines and Gaussian processes
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A brain-computer interface (BCI) is a system that enables control of devices or communication with other persons, only through cerebral activity, without using muscles. The main application for BCIs is assistive technology for disabled persons. Examples fo ...
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining this practice. Thus, when classification uncertainty has to be assessed, it i ...
We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak lear ners which operate on image intensity discriminative features which are defined on small patches and fast to compute. A d ...
Institute of Electrical and Electronics Engineers2009
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining this practice. Thus, when classification uncertainty has to be assessed, it i ...
Biometric identity verification systems frequently face the challenges of non-controlled conditions of data acquisition. Under such conditions biometric signals may suffer from quality degradation due to extraneous, identity-independent factors. It has bee ...
Machine-learning based classification techniques have been shown to be effective at detecting objects in com- plex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically r ...
Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...
Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear ...
Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...
Combining several classifiers has become a very active subdiscipline in the field of pattern recognition. For years, pattern recognition community has focused on seeking optimal learning algorithms able to produce very accurate classifiers. However, empiri ...
