Generalization and Error Bounds
Generalization Error Bounds for Threshold Decision Lists
... the generalization accuracy of classification methods based on the itera- tive use of linear ...the generalization properties of data classification techniques that are based on the use of threshold ...
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A generalization of the modified Simpson’s rule and error bounds
... various error inequalities for this rule. Here we give a generalization of of the modified Simpson’s rule and we also give various error bounds for the generalization ...These ...
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Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
... ization error bounds for propagating one-dimensional distri- butions on graphs and hypergraphs using the 2-Wasserstein ...our generalization bound is the first of its type in the literature of ...
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Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
... The cluster assumption can be interpreted in another way, that is, as the requirement that the decision boundary has to lie in low density regions. This interpretation has been widely used in learning since it can be ...
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Generalization Error Bounds for Bayesian Mixture Algorithms
... similar bounds in the con- text of Gaussian processes, and their relevance to real-world ...our bounds, but a systematic numerical investigation still needs to be ...sample bounds for optimal ...
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Sharp generalization error bounds for randomly-projected classifiers
... chine Learning, Atlanta, Georgia, USA, 2013. JMLR: W&CP volume 28. Copyright 2013 by the author(s). make use of high-probability geometry preservation guarantees via the Johnson-Lindenstrauss lemma (JLL) and ...
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PAC-Bayesian Generalization Error Bounds for Gaussian Process Classification
... We can also compare our main result for sparse GP Gibbs classifiers with state-of-the- art bounds for the popular support vector machine (SVM). This kernel machine is non- probabilistic, due to its ε-insensitive ...
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A Generalization Error for Q-Learning
... average generalization error, finite sample bounds on the difference in average values resulting from different policies are ...approximation error due to the above mentioned ...to ...
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Error bounds for general mixed quasivariational inequalities
... significant generalization of variational inequalities is called the mixed quasivariational inequality involving the nonlinear bifunction which enables us to study the free, mov- ing, unilateral, and equilibrium ...
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Application of Fixed Point Theorem and Error Bounds
... some generalization of Banach’s fixed point , their approximations to the fixed point and error bounds , and also contains some new fixed point theorems and ...
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Refined Error Bounds for Several Learning Algorithms
... excess error rate with O(1/m) asymptotic dependence on m under β-bounded noise: namely s < ...O(1/m) error rates to be achievable by every algorithm of this type for all distributions in the realizable ...
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Mixed quasi variational inequalities involving error bounds
... local/global bounds for the solution of set-valued mixed quasi-variational inequality problems in terms of the residual gap function, the regularized gap function, and the D-gap ...are generalization and ...
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On Ranking and Generalization Bounds
... ”estimation error”, tells us how close the risk of f is to the risk of the best element in the class F ...(”approximation error”) describes how much we lose using the family F ...estimation error, ...
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Generalization bounds for learning the kernel
... fast error rates with respect to the sample number as those in [4, 26, 27, ...ization bounds based on decoupling Gaussian chaos of or- der ...margin bounds using Rademacher ...
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Generalization bounds for learning the kernel
... fast error rates with respect to the sample number as those in [4, 26, 27, ...ization bounds based on decoupling Gaussian chaos of or- der ...margin bounds using Rademacher ...
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Robust Bounds on Generalization from the Margin Distribution
... Despite successes in extending this style of analysis to the agnostic case 2] and applying it to neural networks 2], boosting algorithms 11], perceptron decision trees 13] and Bayesian algorithms 6], there has been ...
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Generalization Bounds for the Area Under an ROC Curve
... a uniform convergence bound for the AUC. Although the result in (Freund et al., 2003) is given only for function classes considered by their RankBoost algorithm, their technique is generally applicable. We state and ...
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Generalization Bounds for the Area Under the ROC Curve
... study generalization properties of the area under the ROC curve (AUC), a quantity that has been advocated as an evaluation criterion for the bipartite ranking ...the error rate used for evaluation in ...
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Generalization Bounds for Ranking Algorithms via Algorithmic Stability
... empirical error in classification or regression, the empirical error in ranking cannot be expressed as a sum of independent random ...convergence bounds for the ranking error, the standard ...
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Classical generalization bounds are surprisingly tight for Deep Networks
... classification error is not a good predictor of the test ...from generalization, defined as convergence of the empirical to the expected ...classical generalization bounds for deep lerning but ...
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