منابع مشابه
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically \optimal" way to select training data. In this paper, we review how optimal data selection techniques have been used with feedforward neural networks. We then show how the same principles may be used to select data for two alternative, statistically-based learning architectures: mixtures of Gaussians and locally we...
متن کاملon some bayesian statistical models in actuarial science with emphasis on claim count
چکیده ندارد.
15 صفحه اولActive Learning with Statistical
For many types of machine learning algorithms, one can compute the statistically \op-timal" way to select training data. In this paper, we review how optimal data selection techniques have been used with feedforward neural networks. We then show how the same principles may be used to select data for two alternative, statistically-based learning ar-chitectures: mixtures of Gaussians and locally ...
متن کاملStatistical Active Learning Algorithms
We describe a framework for designing efficient active learning algorithms that are tolerant to random classification noise and differentially-private. The framework is based on active learning algorithms that are statistical in the sense that they rely on estimates of expectations of functions of filtered random examples. It builds on the powerful statistical query framework of Kearns [30]. We...
متن کاملStatistical Snakes: Active Region Models
This paper describes a new region-growing technique that uses a closed snake driven by a pressure force that is a function of the statistical characteristics of image data. This statistical snake expands until its elements encounter pixels that lie outside user-defined limits relative to a seed region; when these limits are violated the pressure force is reversed to make the model contract. Ten...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 1996
ISSN: 1076-9757
DOI: 10.1613/jair.295