English
Related papers

Related papers: Higher Order Convergent Fast Nonlinear Fourier Tra…

200 papers

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

Although being powerful, the differential transform method yet suffers from a drawback which is how to compute the differential transform of nonlinear non-autonomous functions that can limit its applicability. In order to overcome this…

Classical Analysis and ODEs · Mathematics 2016-12-28 Essam. R. El-Zahar , Abdelhalim Ebaid

This article introduces a new fast direct solver for linear systems arising out of wide range of applications, integral equations, multivariate statistics, radial basis interpolation, etc., to name a few. \emph{The highlight of this new…

Numerical Analysis · Mathematics 2014-07-08 Sivaram Ambikasaran , Eric Darve

The application of error-free transformation (EFT) is recently being developed to solve ill-conditioned problems. It can reduce the number of arithmetic operations required, compared with multiple precision arithmetic, and also be applied…

Numerical Analysis · Mathematics 2019-10-24 Tomonori Kouya

In this paper, we discuss the development of a sublinear sparse Fourier algorithm for high-dimensional data. In ``Adaptive Sublinear Time Fourier Algorithm" by D. Lawlor, Y. Wang and A. Christlieb (2013), an efficient algorithm with…

Numerical Analysis · Mathematics 2019-07-02 Bosu Choi , Andrew Christlieb , Yang Wang

We have evaluated perturbation coefficients of Wilson loops up to $O(g^8)$ for the four-dimensional twisted Eguchi-Kawai model using the numerical stochastic perturbation theory (NSPT) in arXiv:1902.09847. In this talk we present a progress…

High Energy Physics - Lattice · Physics 2020-01-10 Antonio González-Arroyo , Issaku Kanamori , Ken-Ichi Ishikawa , Kanata Miyahana , Masanori Okawa , Ryoichiro Ueno

The recent success of neural networks as implicit representation of data has driven growing interest in neural functionals: models that can process other neural networks as input by operating directly over their weight spaces. Nevertheless,…

Machine Learning · Computer Science 2023-05-24 Allan Zhou , Kaien Yang , Yiding Jiang , Kaylee Burns , Winnie Xu , Samuel Sokota , J. Zico Kolter , Chelsea Finn

In this paper, we introduce a novel approach called the Iterative Aboodh Transform Method (IATM) which utilizes Daftardar--Jafari polynomials for solving non-linear problems. Such method is employed to derive solutions for non-linear…

Numerical Analysis · Mathematics 2025-02-18 Qasim Khan , Anthony Suen

We consider the numerical solution of the discrete multi-marginal optimal transport (MOT) by means of the Sinkhorn algorithm. In general, the Sinkhorn algorithm suffers from the curse of dimensionality with respect to the number of…

Optimization and Control · Mathematics 2023-02-22 Fatima Antarou Ba , Michael Quellmalz

If the phase retrieval problem can be solved by a method similar to that of solving a system of linear equations under the context of FFT, the time complexity of computer based phase retrieval algorithm would be reduced. Here I present such…

Numerical Analysis · Mathematics 2013-05-20 Yuan Sun

We consider the problem of finding the Discrete Fourier Transform (DFT) of $N-$ length signals with known frequency support of size $k$. When $N$ is a power of 2 and the frequency support is a spectral set, we provide an $O(k \log k)$…

Signal Processing · Electrical Eng. & Systems 2021-10-07 P Charantej Reddy , V S S Prabhu Tej , Aditya Siripuram , Brad Osgood

We propose and analyze a versatile and general algorithm called nonlinear forward-backward splitting (NOFOB). The algorithm consists of two steps; first an evaluation of a nonlinear forward-backward map followed by a relaxed projection onto…

Optimization and Control · Mathematics 2021-01-25 Pontus Giselsson

We present a novel algorithm, named the 2D-FFAST, to compute a sparse 2D-Discrete Fourier Transform (2D-DFT) featuring both low sample complexity and low computational complexity. The proposed algorithm is based on mixed concepts from…

Information Theory · Computer Science 2015-09-22 Frank Ong , Sameer Pawar , Kannan Ramchandran

In this work, we extend the fractional linear multistep methods in [C. Lubich, SIAM J. Math. Anal., 17 (1986), pp.704--719] to the tempered fractional integral and derivative operators in the sense that the tempered fractional derivative…

Numerical Analysis · Mathematics 2018-12-11 Ling Guo , Fanhai Zeng , Ian Turner , Kevin Burrage , George Em Karniadakis

In the following document, we present a way to obtain the order of convergence of the Fractional Newton-Raphson (F N-R) method, which seems to have an order of convergence at least linearly for the case in which the order $\alpha$ of the…

Numerical Analysis · Mathematics 2024-03-27 A. Torres-Hernandez , F. Brambila-Paz , U. Iturrarán-Viveros , R. Caballero-Cruz

This paper investigates a class of non-autonomous highly oscillatory ordinary differential equations characterized by a linear component inversely proportional to a small parameter $\varepsilon$, with purely imaginary eigenvalues, and an…

Numerical Analysis · Mathematics 2026-02-05 Zhihao Qi , Weibing Deng , Fuhai Zhu

We present an asymptotically improved algorithm for implementing the Quantum Fourier Transform (QFT) in both the exact and approximate settings. Historically, the approximate QFT has been implemented in $\Theta(n \log n)$ gates, and the…

Quantum Physics · Physics 2025-02-11 Ronit Shah

In this paper we construct high order numerical methods for solving third and fourth orders nonlinear functional differential equations (FDE). They are based on the discretization of iterative methods on continuous level with the use of the…

Numerical Analysis · Mathematics 2024-11-05 Dang Quang A , Dang Quang Long

Bayesian inference, while foundational to probabilistic reasoning, is often hampered by the computational intractability of posterior distributions, particularly through the challenging evidence integral. Conventional approaches like Markov…

Machine Learning · Computer Science 2025-11-11 Di Zhang

A quantum computer directly manipulates information stored in the state of quantum mechanical systems. The available operations have many attractive features but also underly severe restrictions, which complicate the design of quantum…

Quantum Physics · Physics 2015-06-26 Sos S. Agaian , Andreas Klappenecker