[PDF] Top 20 Generalization Error Bounds for Bayesian Mixture Algorithms
Has 10000 "Generalization Error Bounds for Bayesian Mixture Algorithms" found on our website. Below are the top 20 most common "Generalization Error Bounds for Bayesian Mixture Algorithms".
Generalization Error Bounds for Bayesian Mixture Algorithms
... for Bayesian mixture methods, where different regularization criteria may be incorporated, and their effect on the performance can be easily as- ...the bounds obtained are dimension-independent, ... See full document
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Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
... standard algorithms such as Boosting (d’Alch ´e Buc et ...these algorithms, a greater penalization is given to decision boundaries that cross a ...derive generalization error ... See full document
24
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
... mining algorithms on hypergraphs, we investigate in this paper the semi-supervised learning algorithm of propa- gating ”soft labels” ...a generalization applicable to hypergraphs through Wasserstein ... See full document
8
On the generalization of soft margin algorithms
... style bounds, there is considerable slackness in the ...the generalization performance, rather than realistic estimates for the ...motivate algorithms and guide model ... See full document
15
PAC-Bayesian Analysis of Co-clustering and Beyond
... of generalization bounds for the above two problems we found it convenient to apply the PAC-Bayesian framework (McAllester, 1998, 1999), which is reviewed in Section ...PAC-Bayesian ... See full document
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Refined Error Bounds for Several Learning Algorithms
... minimization algorithms to achieve 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 ... See full document
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Microwave Characterization of Dielectric Materials Using Bayesian Neural Networks
... good generalization, the NN designer has to determine the number of hidden neurons (and therefore the number of NN internal ...square error (MSE), between the output of the NN and the one of the training ... See full document
14
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 ... See full document
34
Stability and Generalization in Structured Prediction
... of generalization in structured prediction is by Collins (2001), who developed risk bounds for language parsers using various classical tools, such as the Vapnik-Chervonenkis dimension and margin ...risk ... See full document
52
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
... A learning system consists of data, a learning model and a learning algorithm. The purpose of such a system is to estimate an unknown true density function from data distributed by the true density function. The data ... See full document
30
Dynamics and Generalization Ability of LVQ Algorithms
... rigorous bounds on the generalization error without making explicit assumptions about the learning scenario (for examples in the context of LVQ, see Crammer et ...Such bounds are not ... See full document
38
Breaking the Curse of Dimensionality with Convex Neural Networks
... same generalization error bounds, even when constant-factor approximation cannot be found ...polynomial-time algorithms that preserve the non-exponential sample ... See full document
53
Generalization Error Bounds for Threshold Decision Lists
... theoretical generalization error bounds were derived there, the techniques appeared to perform well in ...tree algorithms FAT, MOC1, and MOC2 due to Bennett et ...the algorithms of ... See full document
29
Algorithmic Stability and Meta-Learning
... estimation error in (6) involves the notion of algorithmic sta- ...tighter bounds. Bousquet and Elisseeff (2002) have shown how generalization error bounds for learning ... See full document
28
Robust Bounds on Generalization from the Margin Distribution
... boosting algorithms 11], perceptron decision trees 13] and Bayesian algorithms 6], there has been concern that the measure of the distribution of margin values attained by the training set is largely ... See full document
28
Inferences under a Class of Finite Mixture Distributions Based on Generalized Order Statistics
... The main purpose of this paper is to obtain estimates of parameters, reliability and hazard rate functions of a heteroge- neous population represented by finite mixture of two general components. The doubly Type ... See full document
14
Generalization of interpolation DFT algorithms and frequency estimators with high image component interference rejection
... Frequency estimation by the IpDFT method is studied in this paper. We have quantitatively analyzed the influ- ences of the interference from the image component and generalized the interpolated DFT algorithms. ... See full document
11
Generalization Bounds for the Area Under the ROC Curve
... For the case of linear ranking functions on R , for which we could compute the bipartite rank- shatter coefficients exactly, we have shown that our uniform convergence bound is considerably tighter than a recent uniform ... See full document
33
Algorithm dependent generalization bounds for multi task learning
... algorithm-dependent generalization bounds, we analyze the performance of one partic- ular task as well as the average performance over all of the multiple tasks for the MTL algorithms, which employ ... See full document
49
Computable error bounds for collocation methods
... This paper deals with error bounds for numerical solutions of linear ordinary differential equations by global or piecewise polynomial collocation methods which are based on consideratio[r] ... See full document
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