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Breakdown Point of Robust Support Vector Machines [PDF]
Entropy, 2017 Support vector machine (SVM) is one of the most successful learning methods for solving classification problems. Despite its popularity, SVM has the serious drawback that it is sensitive to outliers in training samples. The penalty on misclassification is defined by a convex loss called the hinge loss, and the unboundedness of the convex loss causes the ...
Takafumi Kanamori, Shuhei Fujiwara
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Breakdown Point — Examples and Counterexamples
Revstat Statistical Journal, 2007 The breakdown point plays an important though at times controversial role in statistics. In situations in which it has proved most successful there is a group of transformations which act on the sample space and which give rise to an equivariance structure.
Davies, P.L., Gather, U.
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Breakdown of conformal invariance at strongly random critical points [PDF]
Physical Review B, 2001 We consider the breakdown of conformal and scale invariance in random systems with strongly random critical points. Extending previous results on one-dimensional systems, we provide an example of a three-dimensional system which has a strongly random critical point.
Hastings, M. B., Sondhi, S. L.
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ASSESSING ROBUSTNESS OF CLASSIFICATION USING ANGULAR BREAKDOWN POINT. [PDF]
Ann Stat, 2018 Robustness is a desirable property for many statistical techniques. As an important measure of robustness, breakdown point has been widely used for regression problems and many other settings. Despite the existing development, we observe that the standard breakdown point criterion is not directly applicable for many classification problems.
Zhao J, Yu G, Liu Y.
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The finite sample breakdown point of PCS [PDF]
Statistics and Probability Letters, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Eric Schmitt
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The Masking Breakdown Point of Multivariate Outlier Identification Rules [PDF]
Journal of the American Statistical Association, 1999 In this paper, we consider one-step outlier identifiation rules for multivariate data, generalizing the concept of so-called alpha outlier identifiers, as presented in Davies and Gather (1993) for the case of univariate samples. We investigate, how the finite-sample breakdown points of estimators used in these identification rules influence the masking
Claudia Becker, Ursula Gather
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Thermopower as a fingerprint of the Kondo breakdown quantum critical point [PDF]
Physical Review B, 2011 We propose that the thermoelectric power distinguishes two competing scenarios for quantum phase transitions in heavy fermions : the spin-density-wave (SDW) theory and breakdown of the Kondo effect. In the Kondo breakdown scenario, the Seebeck coefficient turns out to collapse from the temperature scale $E^{*}$, associated with quantum fluctuations of ...
Kim, K. -S., Pepin, C.
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Breakdown of Weak-Field Magnetotransport at a Metallic Quantum Critical Point [PDF]
Physical Review Letters, 2005 4 pages, 3 figures RevTeX ...
Fenton, J., Schofield, A. J.
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Some Results on the Spatial Breakdown Point of Robust Point Estimates of the Variogram
Mathematical Geosciences, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
R M Lark
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Finite sample breakdown point of Tukey’s halfspace median [PDF]
Science China Mathematics, 2017 Tukey's halfspace median ($\HM$), servicing as the {multivariate} counterpart of the univariate median, has been introduced and extensively studied in the literature. It is supposed and expected to preserve robustness property (the most outstanding property) of the univariate median.
Yijun Zuo, Qihua Wang
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