Foundations of Modern Statistics

Optimal rates and non-asymptotic bounds in nonparametrics: Z. Harchaoui, A. Juditsky, A. Nemirovski, D. Ostrovskii, Adaptive Denoising of Signals with Local Shift-Invariant Structure.- A. Dubois, Thomas B. Berret, C. Butucea, Goodness-of-fit testing for Hölder continuous densities under local differential privacy.- G. Blanchard and J.ean-Baptiste Fermanian, Nonasymptotic signal detection and two-sample tests in high dimension.- Sara van de Geer and P. Hinz, The Lasso with structured design and entropy of (absolute) convex hulls.- M. Hiabu, E. Mammen and Joseph-Theo Meyer, Local linear smoothing in additive models as data projection.- S. Ayvazyan and V. Ulyanov, A multivariate CLT for "typical" weighted sums with rate of convergence of order O(1/n).- Estimation of matrices and subspaces: F. Götze, A. Tikhomirov, D. Timushev, Rate of convergence for sample covariance sparse matrices.- M. Wahl, Van Trees inequality, group equivariance, and estimation of principal subspaces.- D. Belomestny, E. Krymova, Sparse constrained projection approximation subspace tracking Nonparametric and semiparametric Bayes statistics.- Natalia Bochkina: Bernstein - von Mises theorem and misspecified models: a review.- M. Panov, On accuracy of Gaussian approximation in Bayesian semiparametric problems.- Statistical theory motivated by applications: M. Bl ehaut, X. D'Haultfoeuille, J er emy L'Hour, A. B. Tsybakov, An alternative to synthetic control for models with many covariates under sparsity.- C. Breunig, X. Chen, Adaptive Estimation of Quadratic Functionals in Nonparametric Instrumental Variable Models.- G. Kulaitis, A. Munk and F. Werner, A minimax testing perspective on spatial statistical resolution in microscopy.- Optimisation: P. Dvurechensky, A. Gasnikov, A. Tyurin and V. Zholobov, Unifying Framework for Accelerated Randomized Methods in Convex Optimization.- K. Khowaja, M. Shcherbatyy and W. Karl Härdle. Surrogate Models