[PDF] Top 20 Robust Bounds on Generalization from the Margin Distribution
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Robust Bounds on Generalization from the Margin Distribution
... the distribution of margin values attained by the training set is largely ignored in a bound that depends only on its minimal ...the margin attained by the majority of the ...larger margin as ... See full document
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A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin
... the margin of an example with respect to a classifier is a mea- sure of the confidence of the classification ...the generalization error of a voting classifier that does not depend on how many classifiers ... See full document
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Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin
... butional Margin based Ordinal Embedding (DMOE), which tries to achieve strong generalization performance by opti- mizing the margin distribution in ordinal embedding prob- ...the margin ... See full document
8
Regularization via Mass Transportation
... ideas from distributionally robust optimization, and we give new probabilistic interpretations to existing ...distance from the (discrete) empirical ... See full document
68
Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
... m n. Most existing theoretical studies of supervised classification use empirical processes theory (Devroye et al., 1996; Vapnik, 1998; van de Geer, 2000; Boucheron et al., 2005) to obtain rates of convergence for the ... See full document
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Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes
... the generalization error of classifiers from conv( H ), where H is a fixed VC-class, was achieved by Schapire et ...the generalization ability of classifiers from conv( H ) in terms of the ... See full document
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Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
... ideas from the theory of multi-marginal optimal ...established generalization error bounds for prop- agating one-dimensional distributions using 2-Wasserstein ...first generalization error ... See full document
8
Generalization Bounds for Ranking Algorithms via Algorithmic Stability
... noted from the above discussion, the question of generalization properties of ranking algorithms has so far been investigated mainly in the special setting of bipartite ...of generalization ... See full document
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On the generalization of soft margin algorithms
... Abstract—Generalization bounds depending on the margin of a classifier are a relatively recent ...these bounds has been either their lack of robustness or their ...the generalization of ... See full document
15
Robust bounds for the American put
... or robust, bounds on the prices of exotic op- tions was introduced in Hobson [17] in the context of lookback options, and has been applied several times since; see Brown et ...to bounds on the ... See full document
37
Statistical Learning Theory and Linguistic Typology: a Learnability Perspective on OT’s Strict Domination
... error bounds, that is bounds on the generalization error Err P (f ) of an arbitrary classifier f ∈ F based on parameters such as the shape of f or its perfor- mance on the training set T ...error ... See full document
11
Robust lower bounds for communication and stream computation
... lower bounds lead to lower bounds for a number of data stream problems in the random-order ...such bounds, many of which are tight, for approximating frequency moments, the number of distinct values, ... See full document
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Bounds for the generalization of two mappings related to the Hermite-Hadamard inequality
... In this paper, we give some results concerning the generalization of two mappings associated to the fa- mous Hermite-Hadamard integral inequality for convex functions.. As application, s[r] ... See full document
9
A generalization of the negative binomial distribution
... (GNB) distribution with three parameters α, β and k obtained as a compound form of the generalized Poisson and gamma ...This distribution gives a very close fit for a large number of data and provides an ... See full document
6
An Exceptional Generalization of the Poisson Distribution
... Problem 2. Find an algorithm for generation of ran- dom variates from N(μ, β). The alias method [8] can of course be used for truncated versions, but a tailor-made method would be welcome. Actually, a generation ... See full document
6
ON KEMPTON’S GENERALIZATION OF THE NEGATIVE BINOMIAL DISTRIBUTION
... Poisson distribution is of interest on its own because mixed Poisson distributions is an important class of distributions for the statistical analysis of over-dispersed (variance exceeding the mean) count ... See full document
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Bounds for the approximation of Poisson binomial distribution by Poisson distribution
... structure and therefore they are used to being approximated by Poisson distribution. Well-known Le Cam’s inequality is established for providing information on the quality of a Poisson approximation. The main aim ... See full document
10
Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees
... dataset from (Parikh and Grauman 2011) is used in this ...images from 8 scene categories, which are described by high level attribute ...1. From Table 1, it is seen that the performance of some meth- ... See full document
8
Robust Semantic Parsing with Adversarial Learning for Domain Generalization
... more robust classifier using predicate and context embeddings to perform frame identifica- ...the generalization issue within the framework of a sequence tagging semantic frame parser that performs frame ... See full document
8
Application and Generalization of Eigenvalues Perturbation Bounds for Hermitian Block Tridiagonal Matrices
... perturbation bounds via bounding eigenvector components ...perturbation bounds for the singular values of the block tridiagonal matrix via applying the ideas in paper ...perturbation bounds when the ... See full document
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