منابع مشابه
Machine Learning in Applied Statistics
This special issue of Model Assisted Statistics and Applications (MASA) focused on knowing how current machine learning methods can be applied to diverse statistics areas. We have ten papers about the recent machine learning developments and applications, including survey sampling, biostatistics, bioinformatics, genetics, time series analysis, and technology forecasting. The issue starts with a...
متن کاملProximal Algorithms in Statistics and Machine Learning
In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closedform solutions of proximal operators and envelope representations based on the Moreau, Forward-Backward, Douglas-Rachford and Half-Quadratic envelopes. Envelope repres...
متن کاملAlgorithmic Statistics, Prediction and Machine Learning
Algorithmic statistics considers the following problem: given a binary string x (e.g., some experimental data), find a “good” explanation of this data. It uses algorithmic information theory to define formally what is a good explanation. In this paper we extend this framework in two directions. First, the explanations are not only interesting in themselves but also used for prediction: we want ...
متن کاملAppendix : Machine Learning Bias Versus Statistical Bias
is if and 0 if. This high variance may help to explain why there is selection pressure for weak (machine learning) bias when the (machine learning) bias correctness is low. The reason that statisticians are interested in (statistical) bias and variance is that squared error is equal to the sum of squared (statistical) bias and variance. Therefore minimal (statistical) bias and minimal variance ...
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ژورنال
عنوان ژورنال: Nature Methods
سال: 2018
ISSN: 1548-7091,1548-7105
DOI: 10.1038/nmeth.4642