{ "id": "2101.03665", "version": "v1", "published": "2021-01-11T02:15:02.000Z", "updated": "2021-01-11T02:15:02.000Z", "title": "On the power of standard information for tractability for $L_2$-approximation in the randomized setting", "authors": [ "Wanting Lu", "Heping Wang" ], "comment": "25 pages", "categories": [ "math.NA", "cs.NA" ], "abstract": "We study approximation of multivariate functions from a separable Hilbert space in the randomized setting with the error measured in the weighted $L_2$ norm. We consider algorithms that use standard information $\\Lambda^{\\rm std}$ consisting of function values or general linear information $\\Lambda^{\\rm all}$ consisting of arbitrary linear functionals. We use the weighted least squares regression algorithm to obtain the upper estimates of the minimal randomized error using $\\Lambda^{\\rm std}$. We investigate the equivalences of various notions of algebraic and exponential tractability for $\\Lambda^{\\rm std}$ and $\\Lambda^{\\rm all}$ for the normalized or absolute error criterion. We show that in the randomized setting for the normalized or absolute error criterion, the power of $\\Lambda^{\\rm std}$ is the same as that of $\\Lambda^{\\rm all}$ for all notions of exponential and algebraic tractability without any condition. Specifically, we solve four Open Problems 98, 100-102 as posed by E.Novak and H.Wo\\'zniakowski in the book: Tractability of Multivariate Problems, Volume III: Standard Information for Operators, EMS Tracts in Mathematics, Z\\\"urich, 2012.", "revisions": [ { "version": "v1", "updated": "2021-01-11T02:15:02.000Z" } ], "analyses": { "subjects": [ "41A63", "65C05", "65D15", "65Y20" ], "keywords": [ "standard information", "randomized setting", "tractability", "absolute error criterion", "approximation" ], "note": { "typesetting": "TeX", "pages": 25, "language": "en", "license": "arXiv", "status": "editable" } } }