Results 271 to 280 of about 262,287 (308)

Margin Distribution Bounds on Generalization

1999
A number of results have bounded generalization of a classi fier in terms of its margin on the training points. There has been some debate about whether the minimum margin is the best measure of the distribution of training set margin values with which to estimate the generalization.
John Shawe-Taylor, Nello Cristianini
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A New Bivariate Distribution with Rayleigh and Lindley Distributions as Marginals

Journal of Statistical Theory and Practice, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thomas, P. Yageen, Jose, Jitto
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Large Margin Distribution Learning

2014
Support vector machines (SVMs) and Boosting are possibly the two most popular learning approaches during the past two decades. It is well known that the margin is a fundamental issue of SVMs, whereas recently the margin theory for Boosting has been defended, establishing a connection between these two mainstream approaches.
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Bounds on margin distributions inBlearningBproblems

Annales de l?Institut Henri Poincare (B) Probability and Statistics, 2003
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A Reformulation of the Marginal Productivity Theory of Distribution

Econometrica, 1984
Reformulating marginal productivity theory by replacing productivity with respect to commodities with productivity with respect to persons and then defining perfectly competitive equilibrium as an allocation at which each person receives the marginal product of his/her contribution - called a no-surplus allocation - there emerges a competitive theory ...
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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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On generalized-marginal time-frequency distributions

IEEE Transactions on Signal Processing, 1996
We introduce a family of time-frequency (TF) distributions with generalized marginals, i.e., beyond the time-domain and the frequency-domain marginals, in the sense that the projections of a TF distribution along one or more angles are equal to the magnitude squared of the fractional Fourier transforms of the signal.
Xiang-Gen Xia 0001, Yuri Owechko, Bernard H. Soffer, Roy M. Matic   +3 more
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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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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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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