Jan 6, 2016 - where K and M are positive semidefinite and one of them is definite. Given a pair of approximate deflating subspaces of {K, M}, it can be shown ...
The derivations of existing error bounds for reduced order models of time varying ... POD reduced order model of various linear and nonlinear parabolic PDEs ...
3. Abstract. In this paper, we attempt to extend the definition and existing local error ...... 455. In Dynamical systems (Proc. Sympos., Univ. Bahia, Salvador, 1971).
Consider a two-station tandem system with capacity constraints for at most Ni ...... product-form is violated since when the second station is saturated (n2 = N2), ...
May 23, 2012 - ءءء xn yn. أ. , where x ¼ ًx1, x2, ..., xnق, y ¼ ًy1, y2, ..., ynق2ًR قn . Then ًX, dأق is a multiplicative metric space. Definition 2.2 ([2]) Let (X, d) be a ...
equation, namely Dirichlet, Neumann or Robin boundary conditions; these conditions ...... [15] K.W. Morton and E. Süli (1991), Finite volume methods and their ...
Jul 17, 2012 - CO] 17 Jul 2012. BOUNDS FOR APPROXIMATE. DISCRETE TOMOGRAPHY SOLUTIONS. LAJOS HAJDU AND ROB TIJDEMAN. Abstract.
at Akamai Techologies, Inc., Cambridge, MA 02139. 1 Introduction. Clustering is a fundamental problem in unsupervised learn- ing that has found application in ...
Lower bounds for approximate factorizations via semidefinite programming (extended abstract)*. Erich Kaltofen,1 Bin Li,2 Kartik Sivaramakrishnan,1 Zhengfeng ...
the data of the solutions in the semi-group sense as introduced in [2] are given: these estimates yield an estimate between u and uε of order ε1/2 in the case of ...
the single composite node which represents the aggregated subnetwork in terms ... model belongs to the restricted class of product-form queueing networks [4], it is ... the process matrix [5,7,8,17,18,21) and aggregation methods dyrectly ..... [17] S
Mar 16, 2014 - nonadditive codes are especially suitable for the error correction of ... requires the use of suitable error mitigation techniques. ...... 1 â γ |e18ã. â.
Error Bounds for Correlation Clustering. Thorsten Joachims [email protected].
Cornell University, Dept. of Computer Science, 4153 Upson Hall, Ithaca, NY ...
Some new types of primal space derivative-like objects â ... Let f : X â Y where X is a metric space and Y is a real normed linear space. ...... Asplund spaces.
Feb 13, 2014 - is affected by several factors such as satellite clock error, propagation path delays and ... All satellites contain atomic clocks that control all on-.
Nov 13, 2009 - [18] Jianqing Fan, On the optimal rates of convergence for nonparametric deconvolution problems,. Ann. Statist. 19 (1991), no. 3, 1257â1272.
The subject of bounding the angle between an invariant subspace of a ... invariant subspace with the p dimensional subspace Y . The question which rises.
Error Bounds for Transductive Learning via. Compression and Clustering. Philip Derbeko. Ran El-Yaniv. Ron Meir. Technion - Israel Institute of Technology.
1. Introduction. This paper studies various error bounds for the following inclusion problem in mathematical optimization: given g and K, find x such that g x â K,.
May 1, 2013 - A variety of examples is provided. 1 Introduction. We consider a linear differential operator D of order k in d real variables in the notation. Df = â.
It is a standard result in the theory of quantum error-correcting codes that no .... Wegman and Carter [6] have suggested several FUHFs for the special case M = {0, ..... Now, the adversary is left with the task of mounting a quantum attack against .
Jan 29, 2014 - arXiv:1401.7658v1 [quant-ph] 29 Jan 2014 ... show that the optimal asymptotic rate must lie between C/2 and C. Secondly, we show ..... + pr = 1 then we say that {Ak} forms a set of weighted states. ...... below by the square of the opt
Feb 15, 2013 - Theorem 3.1 (Titchmarsh-Riesz). [17, p. 92] Let ...... [7] Alan F. Beardon, Algebra and geometry, Cambridge University Press, Cambridge, 2005.
Suprema of empirical processes (statistics, learning theory). Z = sup fâF. â f(Xi). ..... Empirical risk minimization (ERM): approximate the risk by. Ln(g) = 1 n. â n.
The approximate solution of quasilinear elliptic boundary value problems by
linear .... a method for computing highly accurate numerical solutions. Rather, it is
.
