scientific article; zbMATH DE number 1950575
From MaRDI portal
zbMath1019.68093MaRDI QIDQ4413261
Publication date: 17 July 2003
Full work available at URL: http://link.springer.de/link/service/series/0558/bibs/2600/26000001.htm
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Inequalities; stochastic orderings (60E15) Learning and adaptive systems in artificial intelligence (68T05) Signal detection and filtering (aspects of stochastic processes) (60G35) Statistical aspects of information-theoretic topics (62B10)
Related Items
The shattering dimension of sets of linear functionals., Complexity regularization via localized random penalties, Sampling discretization and related problems, On the geometry of polytopes generated by heavy-tailed random vectors, Convergence of the Weighted Nonlocal Laplacian on Random Point Cloud, Imaging conductivity from current density magnitude using neural networks*, A refined Hoeffding's upper tail probability bound for sum of independent random variables, An axiomatic approach to intrinsic dimension of a dataset, Asymptotic properties of neural network sieve estimators, Regularized learning schemes in feature Banach spaces, Consistency of spectral clustering, Approximating the covariance ellipsoid, A recursive procedure for density estimation on the binary hypercube, Refined Rademacher Chaos Complexity Bounds with Applications to the Multikernel Learning Problem, Foundations of Support Constraint Machines, Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses, Learning bounds of ERM principle for sequences of time-dependent samples, Kernel methods in machine learning, Obtaining fast error rates in nonconvex situations, Unregularized online learning algorithms with general loss functions, Dimension reduction by random hyperplane tessellations, Aspects of discrete mathematics and probability in the theory of machine learning, Sequential complexities and uniform martingale laws of large numbers, Monte Carlo algorithms for optimal stopping and statistical learning, Empirical minimization, Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization, Sampling discretization error of integral norms for function classes, Estimation in High Dimensions: A Geometric Perspective, Oracle inequalities for support vector machines that are based on random entropy numbers, Theory of Classification: a Survey of Some Recent Advances, On the Optimality of Sample-Based Estimates of the Expectation of the Empirical Minimizer, Generalization Error of Minimum Weighted Norm and Kernel Interpolation, Integer cells in convex sets