Pages that link to "Item:Q1323283"

The following pages link to Rates of convergence for empirical processes of stationary mixing sequences (Q1323283):

Displaying 50 items.

• Estimation of semivarying coefficient time series models with ARMA errors (Q309731) (← links)
• An oracle inequality for regularized risk minimizers with strongly mixing observations (Q373424) (← links)
• Strong approximation results for the empirical process of stationary sequences (Q378823) (← links)
• On a clustering criterion for dependent observations (Q389296) (← links)
• Generalization bounds of ERM algorithm with Markov chain samples (Q403479) (← links)
• Asymptotic normality of Powell's kernel estimator (Q421405) (← links)
• Learning from regularized regression algorithms with \(p\)-order Markov chain sampling (Q423185) (← links)
• Generalization bounds of ERM algorithm with \(V\)-geometrically ergodic Markov chains (Q429786) (← links)
• Learning performance of Tikhonov regularization algorithm with geometrically beta-mixing observations (Q619769) (← links)
• Regularized least-squares regression: learning from a sequence (Q645620) (← links)
• Classification with non-i.i.d. sampling (Q652859) (← links)
• Generalization performance of least-square regularized regression algorithm with Markov chain samples (Q662073) (← links)
• A sequential empirical CLT for multiple mixing processes with application to \(\mathcal{B}\)-geometrically ergodic Markov chains (Q743520) (← links)
• Generalization performance of Lagrangian support vector machine based on Markov sampling (Q830752) (← links)
• On mixing rate and convergence to stationary regime in discrete time Erlang problem (Q845467) (← links)
• Estimating beta-mixing coefficients via histograms (Q902219) (← links)
• Unsupervised slow subspace-learning from stationary processes (Q950200) (← links)
• Constructing processes with prescribed mixing coefficients (Q956363) (← links)
• Uniform convergence of Vapnik-Chervonenkis classes under ergodic sampling (Q989178) (← links)
• Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path (Q1009248) (← links)
• Learning from uniformly ergodic Markov chains (Q1023402) (← links)
• Rates of convergence for classes of functions: The non-i.i.d. case (Q1083113) (← links)
• Invariance principles for absolutely regular empirical processes (Q1347273) (← links)
• \(M\)-type regression splines involving time series (Q1360970) (← links)
• The bootstrap for empirical processes based on stationary observations (Q1382489) (← links)
• Rates of uniform convergence for empirical processes of strictly stationary \(\beta\)-mixing sequences indexed by an unbounded class of functions. (Q1609731) (← links)
• Simpler PAC-Bayesian bounds for hostile data (Q1640576) (← links)
• A novel partial-linear single-index model for time series data (Q1727926) (← links)
• Factor models for asset returns based on transformed factors (Q1739597) (← links)
• A note on uniform laws of averages for dependent processes (Q1801875) (← links)
• Rates of uniform convergence of empirical means with mixing processes (Q1871232) (← links)
• Some remarks on coupling of dependent random variables (Q1871329) (← links)
• The generalization performance of ERM algorithm with strongly mixing observations (Q1959486) (← links)
• Consistent online Gaussian process regression without the sample complexity bottleneck (Q2058904) (← links)
• Empirical process theory for locally stationary processes (Q2073222) (← links)
• A statistical learning perspective on switched linear system identification (Q2081825) (← links)
• Convergence of de Finetti's mixing measure in latent structure models for observed exchangeable sequences (Q2091819) (← links)
• Nonparametric regression for locally stationary random fields under stochastic sampling design (Q2137017) (← links)
• Empirical process theory for nonsmooth functions under functional dependence (Q2154954) (← links)
• Policy space identification in configurable environments (Q2163245) (← links)
• Discrepancy-based theory and algorithms for forecasting non-stationary time series (Q2188766) (← links)
• On the unbiased asymptotic normality of quantile regression with fixed effects (Q2190248) (← links)
• On the sample complexity of the linear quadratic regulator (Q2194770) (← links)
• Lasso guarantees for \(\beta \)-mixing heavy-tailed time series (Q2196212) (← links)
• Empirical risk minimization and complexity of dynamical models (Q2215723) (← links)
• Learning performance of regularized regression with multiscale kernels based on Markov observations (Q2244161) (← links)
• Sequential complexities and uniform martingale laws of large numbers (Q2257118) (← links)
• Mixing time estimation in reversible Markov chains from a single sample path (Q2330466) (← links)
• Central limit theorems for conditional empirical and conditional \(U\)-processes of stationary mixing sequences (Q2335548) (← links)
• Generalization performance of Gaussian kernels SVMC based on Markov sampling (Q2339390) (← links)