Results 251 to 260 of about 1,381,183 (287)

Multitaper marginal time–frequency distributions

Signal Processing, 2006
Time-frequency distributions (TFDs) belonging to Cohen's class yield a frequency marginal that is equivalent to the periodogram of the signal. It is well-known that the periodogram is not a good spectral estimator since it is not a consistent estimate, i.e. its variance does not decrease with the sample size. Thomson addressed this issue by introducing
Selin Aviyente, William J. Williams
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Margin distribution based bagging pruning

Neurocomputing, 2012
Bagging is a simple and effective technique for generating an ensemble of classifiers. It is found there are a lot of redundant base classifiers in the original Bagging. We design a pruning approach to bagging for improving its generalization power. The proposed technique introduces the margin distribution based classification loss as the optimization ...
Zongxia Xie, Yong Xu 0007, Qinghua Hu, Pengfei Zhu 0001   +3 more
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On the Existence of Probability Distributions with Given Marginals

Theory of Probability & Its Applications, 2004
Summary: Let \(X=\{0,\ldots, n-1\}\) and \(\Gamma=\{(x_1,\ldots, x_s)\in X^s:\,\sum_{\sigma=1}^s x_\sigma=n-1\}\). For the marginals of probability distributions on \(\Gamma\) with the additional property of forming an \(s\)-tuple of decreasing probabilities on \(X\) a simple characterization is given.
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Multiview Large Margin Distribution Machine

IEEE Transactions on Neural Networks and Learning Systems
Margin distribution has been proven to play a crucial role in improving generalization ability. In recent studies, many methods are designed using large margin distribution machine (LDM), which combines margin distribution with support vector machine (SVM), such that a better performance can be achieved.
Kun Hu, Yingyuan Xiao, Wenguang Zheng, Wenxin Zhu, Ching-Hsien Hsu   +4 more
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A Bivariate Marginal Distribution Genetic Model

2006 IEEE International Conference on Evolutionary Computation, 2006
We introduce a genetic model based on simulated crossover of fixed sequences of two bit genes. States and dynamics of the deterministic genetic system, represented by the model , are derived in the case of infinite populations and for finite fitness functions (expressed in terms of multivariate polynomials).
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A Note on Multivariate Distributions with Specified Marginals

Journal of the Operational Research Society, 1988
Johnson and Tenenbein describe a procedure for generating random values from a bivariate distribution with specified marginal forms and any required correlation between the two variables. This note shows that the approach can be extended to produce values from general multivariate distributions in a straightforward manner.
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A Marginal Effects Approach to Interpreting Main Effects and Moderation

Organizational Research Methods, 2022
John R Busenbark, Scott D Graffin, Robert J Campbell   +2 more
exaly  

Margin Distribution and Soft Margin

2000
John Shawe-Taylor, Nello Christianini
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A bivariate distribution with convolution of binomials as marginals

Communications in Statistics - Simulation and Computation, 2023
Seng Huat Ong, Shin Zhu Sim
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Using Predictions and Marginal Effects to Compare Groups in Regression Models for Binary Outcomes

Sociological Methods and Research, 2021
Sarah A Mustillo
exaly