APPROXIMATIONS OF CONVEX BODIES BY POLYTOPES AND BY PROJECTIONS OF SPECTRAHEDRA Alexander Barvinok April 2012 Abstract. We prove that for any compact set B ⊂ Rd and for any ǫ > 0 there is a

Source URL: www.math.lsa.umich.edu

• Algebra
• Mathematics
• Linear algebra
• Mathematical analysis
• Convex analysis
• Mathematical optimization
• Real algebraic geometry
• Matrices
• Semidefinite programming
• Convex cone
• Matrix
• Convex function

INVESTIGATION OF 3He(p, 2p)d REACTION IN T-MATRIX AND DIFFRACTION APPROXIMATIONS AT INTERMEDIATE ENERGIES V. V. Davydovskyy, A. D. Foursat In the framework of Т-matrix approximation with distorted waves, as well as with

Source URL: jnpae.kinr.kiev.ua

Stochastic Methods for Finite Approximations in a non-Archimedean Setting Trond Digernes1 Joint work with Erik M. Bakken1 and David Weisbart2 1 Department of Mathematical Sciences The Norwegian University of Science and

Source URL: p-adics2015.matf.bg.ac.rs

Optimal rates for random Fourier feature kernel approximations∗ Zolt´an Szab´o (Gatsby Unit, University College London)† Abstract: Kernel methods represent one of the most powerful tools in machine learning to tac

Source URL: www.gatsby.ucl.ac.uk

Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling Peter Hooper Yasin Abbasi-Yadkori, Russ Greiner, Bret Hoehn Dept of Mathematical & Statistical Sciences

Source URL: webdocs.cs.ualberta.ca

Training Restricted Boltzmann Machines using Approximations to the Likelihood Gradient Tijmen Tieleman Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada

Source URL: www.cs.utoronto.ca

Introduction Variational Approximations On the Properties of Variational Approximations in Statistical Learning. Pierre Alquier

Source URL: alquier.ensae.net

MAXIMUM ENTROPY GAUSSIAN APPROXIMATIONS FOR THE NUMBER OF INTEGER POINTS AND VOLUMES OF POLYTOPES Alexander Barvinok and J.A. Hartigan January 2010

Source URL: www.math.lsa.umich.edu

• Statistics
• Mathematical analysis
• Probability
• Probability distributions
• Information theory
• Randomness
• Infinitely divisible probability distributions
• Normal distribution
• Central limit theorem
• Entropy
• Geometric distribution
• Expected value

First version: December 17, 1996 Revised version: May 26, 1998 EXPONENTIAL APPROXIMATIONS IN COMPLETELY REGULAR TOPOLOGICAL SPACES AND EXTENSIONS OF SANOV’S THEOREM

Source URL: www.fam.tuwien.ac.at

Optimal rates for random Fourier feature approximations∗ Zolt´an Szab´o (Gatsby Unit, University College London)† Abstract: Kernel methods represent one of the most powerful tools in machine learning to tackle

Source URL: www.gatsby.ucl.ac.uk