Interpolation of Random Hyperplanes

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Interpolation of Random Hyperplanes

Let {(Zi,Wi) : i = 1, . . . , n} be uniformly distributed in [0, 1]d × G(k, d), where G(k, d) denotes the space of k-dimensional linear subspaces of Rd. For a differentiable function f : [0, 1]k → [0, 1]d, we say that f interpolates (z,w) ∈ [0, 1]d × G(k, d) if there exists x ∈ [0, 1]k such that f(x) = z and ~ f(x) = w, where ~ f(x) denotes the tangent space at x defined by f . For a smoothness...

متن کامل

On Random Interpolation

In a recent paper Salem and Zygmund [1] proved the following result : Put 2TCv a " = avn~ _ 2n (v = 0, 1,. . ., 2n)-{-1 and denote the 99,'(t) the v-th Rademacher function. Denote by L.(t, 0) the unique trigonometric polynomial (in 0) of degree not exceeding n for Denote Mjt) = max I L,, (t, 0)1. Then for almost all t 050<2a M,, t) lim BLOCKIN~ <_ 2. (log n)a n=~ P. ERDÖS I am going to prove th...

متن کامل

Bayes Optimal Hyperplanes! Maximal Margin Hyperplanes

Maximal margin classifiers are a core technology in modern machine learning. They have strong theoretical justifications and have shown empirical successes. We provide an alternative justification for maximal margin hyperplane classifiers by relating them to Bayes optimal classifiers that use Parzen windows estimations with Gaussian kernels. For any value of the smoothing parameter (the width o...

متن کامل

A feasible interpolation for random resolution

We show how to apply the general feasible interpolation theorem for semantic derivations from [6] to random resolution defined by [3]. As a consequence we get a lower bound for random resolution refutations of the clique-coloring formulas. Assume A1, . . . , Am, B1, . . . , Bl is an unsatisfiable set of clauses in variables partitioned into three disjoint sets p, q and r, with clauses Ai contai...

متن کامل

Kriging for interpolation in random simulation

Whenever simulation requires much computer time, interpolation is needed. There are several interpolation techniques in use (for example, linear regression), but this paper focuses on Kriging. This technique was originally developed in geostatistics by D. G. Krige, and has recently been widely applied in deterministic simulation. This paper, however, focuses on random or stochastic simulation. ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Electronic Journal of Probability

سال: 2007

ISSN: 1083-6489

DOI: 10.1214/ejp.v12-435