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The Fast Reciprocal Square Root Algorithm is a well-established approximation technique consisting of two stages: first, a coarse approximation is obtained by manipulating the bit pattern of the floating point argument using integer…

Numerical Analysis · Mathematics 2023-07-31 Mike Day

The recently proposed soft finite element method (SoftFEM) reduces the stiffness (condition numbers), consequently improving the overall approximation accuracy. The method subtracts a least-square term that penalizes the gradient jumps…

Numerical Analysis · Mathematics 2024-02-27 Jipei Chen , Victor M. Calo , Quanling Deng

In this paper we develop the Greedy Recombination Interpolation Method (GRIM) for finding sparse approximations of functions initially given as linear combinations of some (large) number of simpler functions. In a similar spirit to the…

Numerical Analysis · Mathematics 2024-03-11 Terry Lyons , Andrew D. McLeod

Fast convolution algorithms, including Winograd and FFT, can efficiently accelerate convolution operations in deep models. However, these algorithms depend on high-precision arithmetic to maintain inference accuracy, which conflicts with…

Machine Learning · Computer Science 2024-07-04 Liulu He , Yufei Zhao , Rui Gao , Yuan Du , Li Du

Given a graphical model (GM), computing its partition function is the most essential inference task, but it is computationally intractable in general. To address the issue, iterative approximation algorithms exploring certain local…

Machine Learning · Computer Science 2019-05-15 Sejun Park , Eunho Yang , Se-Young Yun , Jinwoo Shin

We give a deterministic polynomial-time approximation scheme (FPTAS) for the volume of the truncated fractional matching polytope for graphs of maximum degree $\Delta$, where the truncation is by restricting each variable to the interval…

Data Structures and Algorithms · Computer Science 2024-09-12 Heng Guo , Vishvajeet N

We present a new algorithm, FRiM (FRactal Iterative Method), aiming at the reconstruction of the optical wavefront from measurements provided by a wavefront sensor. As our application is adaptive optics on extremely large telescopes, our…

Mathematical Physics · Physics 2015-05-18 Eric Thiebaut , Michel Tallon

Recent progress in synthetic aperture sonar (SAS) technology and processing has led to significant advances in underwater imaging, outperforming previously common approaches in both accuracy and efficiency. There are, however, inherent…

Numerical Analysis · Mathematics 2017-06-28 John McKay , Anne Gelb , Vishal Monga , Raghu Raj

Polynomial reproduction plays a relevant role in deriving error estimates for various approximation schemes. Local reproduction in a quasi-uniform setting is a significant factor in the estimation of error and the assessment of stability…

Numerical Analysis · Mathematics 2024-11-25 Stefano De Marchi , Giacomo Cappellazzo

The problem of computing a representation for a real polynomial as a sum of minimum number of squares of polynomials can be casted as finding a symmetric positive semidefinite real matrix (Gram matrix) of minimum rank subject to linear…

Optimization and Control · Mathematics 2011-01-28 Yue Ma , Lihong Zhi

In this paper, we introduce a superconvergent approximation method that employs radial basis functions (RBFs) in the numerical solution of conservation laws. The use of RBFs for interpolation and approximation is a well developed area of…

Numerical Analysis · Mathematics 2021-06-21 Andrew Christlieb , William Sands , Hyoseon Yang

An effective means to approximate an analytic, nonperiodic function on a bounded interval is by using a Fourier series on a larger domain. When constructed appropriately, this so-called Fourier extension is known to converge geometrically…

Numerical Analysis · Mathematics 2013-05-14 Ben Adcock , Daan Huybrechs , Jesus Martin-Vaquero

The functional generalized additive model (FGAM) provides a more flexible nonlinear functional regression model than the well-studied functional linear regression model. This paper restricts attention to the FGAM with identity link and…

Statistics Theory · Mathematics 2013-01-22 Xiao Wang , David Ruppert

We present a new algorithm for solving optimization problems with objective functions that are the sum of a smooth function and a (potentially) nonsmooth regularization function, and nonlinear equality constraints. The algorithm may be…

Optimization and Control · Mathematics 2024-04-12 Yutong Dai , Xiaoyi Qu , Daniel P. Robinson

Computationally efficient numerical methods for high-order approximations of convolution integrals involving weakly singular kernels find many practical applications including those in the development of fast quadrature methods for…

Numerical Analysis · Mathematics 2018-10-10 Akash Anand , Awanish Kumar Tiwari

Orthogonal frequency-division multiplexing (OFDM) has been selected as the basis for the fifth-generation new radio (5G-NR) waveform developments. However, effective signal processing tools are needed for enhancing the OFDM spectrum in…

Signal Processing · Electrical Eng. & Systems 2024-10-30 Juha Yli-Kaakinen , AlaaEddin Loulou , Toni Levanen , Kari Pajukoski , Arto Palin , Markku Renfors , Mikko Valkama

The goal in {\em reconfiguration problems} is to compute a {\em gradual transformation} between two feasible solutions of a problem such that all intermediate solutions are also feasible. In the {\em Matching Reconfiguration Problem} (MRP),…

Data Structures and Algorithms · Computer Science 2020-05-07 Noam Solomon , Shay Solomon

An algorithm for generating interpolants for formulas which are conjunctions of quadratic polynomial inequalities (both strict and nonstrict) is proposed. The algorithm is based on a key observation that quadratic polynomial inequalities…

Logic in Computer Science · Computer Science 2016-11-14 Ting Gan , Liyun Dai , Bican Xia , Naijun Zhan , Deepak Kapur , Mingshuai Chen

Radial Basis Function-generated Finite Differences (RBF-FD) is a meshless method that can be used to numerically solve partial differential equations. The solution procedure consists of two steps. First, the differential operator is…

Numerical Analysis · Mathematics 2026-02-26 Andrej Kolar-Požun , Mitja Jančič , Gregor Kosec

In a common formulation of semi-infinite programs, the infinite constraint set is a requirement that a function parametrized by the decision variables is nonnegative over an interval. If this function is sufficiently closely approximable by…

Optimization and Control · Mathematics 2017-03-24 Dávid Papp