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Related papers: Nested ansatz method for Baker-Akhiezer functions

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This paper presents a new algorithm, termed \emph{truncated amplitude flow} (TAF), to recover an unknown vector $\bm{x}$ from a system of quadratic equations of the form $y_i=|\langle\bm{a}_i,\bm{x}\rangle|^2$, where $\bm{a}_i$'s are given…

Machine Learning · Statistics 2017-08-22 Gang Wang , Georgios B. Giannakis , Yonina C. Eldar

We provide a novel statistical perspective on a classical problem at the intersection of computer science and information theory: recovering the empirical frequency of a symbol in a large discrete dataset using only a compressed…

Methodology · Statistics 2025-04-11 Mario Beraha , Stefano Favaro , Matteo Sesia

The Barzilai-Borwein (BB) method is a popular and efficient tool for solving large-scale unconstrained optimization problems. Its search direction is the same as for the steepest descent (Cauchy) method, but its stepsize rule is different.…

Optimization and Control · Mathematics 2019-11-13 Oleg Burdakov , Yu-Hong Dai , Na Huang

Let X and Y be separable metrizable spaces, and f:X-->Y be a function. We want to recover f from its values on a small set via a simple algorithm. We show that this is possible if f is Baire class one, and in fact we get a characterization.…

Logic · Mathematics 2007-10-02 Dominique Lecomte

The minimization of the action of a QFT with a constraint dictated by the block averaging procedure is an important part of Ba{\l}aban's approach to renormalization. It is particularly interesting for QFTs with non-trivial target spaces,…

Mathematical Physics · Physics 2024-03-18 Wojciech Dybalski , Alexander Stottmeister , Yoh Tanimoto

In Neural Networks (NN), Adaptive Activation Functions (AAF) have parameters that control the shapes of activation functions. These parameters are trained along with other parameters in the NN. AAFs have improved performance of Neural…

Computer Vision and Pattern Recognition · Computer Science 2016-08-24 Le Hou , Dimitris Samaras , Tahsin M. Kurc , Yi Gao , Joel H. Saltz

We prove various theorems on approximation using polynomials with integer coefficients in the Bernstein basis of any given order. In the extreme, we draw the coefficients from $\{ \pm 1\}$ only. A basic case of our results states that for…

Information Theory · Computer Science 2022-12-08 C. Sinan Güntürk , Weilin Li

The main result of this paper is a far reaching generalization of the completeness result given by V.~Katsnelson in a recent paper [35]. Instead of just using a collection of dilated Gaussians it is shown that the key steps of an earlier…

Functional Analysis · Mathematics 2022-03-22 Hans G. Feichtinger , Anupam Gumber

Nested sampling (NS) is a popular algorithm for Bayesian computation. We investigate statistical errors in NS both analytically and numerically. We show two analytic results. First, we show that the leading terms in Skilling's expression…

Instrumentation and Methods for Astrophysics · Physics 2023-03-29 Andrew Fowlie , Qiao Li , Huifang Lv , Yecheng Sun , Jia Zhang , Le Zheng

We show that there exists an entire function f without zeros for which the associated Newton function N(z)=z-f(z)/f'(z) is a transcendental meromorphic functions without Baker domains. We also show that there exists an entire function f…

Complex Variables · Mathematics 2010-06-22 Walter Bergweiler

The Bayesian methods for linear inverse problems is studied using hierarchical Gaussian models. The problems are considered with different discretizations, and we analyze the phenomena which appear when the discretization becomes finer. A…

Statistics Theory · Mathematics 2009-09-14 Tapio Helin , Matti Lassas

We give conditions for local diagonalization of analytic operator families acting between real or complex Banach spaces. The transformations are constructed from an operator Toeplitz matrix obtained from Jordan chains of increasing length.…

Algebraic Geometry · Mathematics 2023-05-24 Matthias Stiefenhofer

For N=1 supersymmetric quantum electrodynamics, regularized by higher derivatives, a method for summation of all Feynman diagrams defining the beta-function is presented. Using this method we prove that the beta-function is given by an…

High Energy Physics - Theory · Physics 2011-08-04 K. V. Stepanyantz

Neural additive model (NAM) is a recently proposed explainable artificial intelligence (XAI) method that utilizes neural network-based architectures. Given the advantages of neural networks, NAMs provide intuitive explanations for their…

Machine Learning · Computer Science 2024-11-12 Hoki Kim , Jinseong Park , Yujin Choi , Seungyun Lee , Jaewook Lee

We examine four different notions of variation for real-valued functions defined on the compact ring of integers of a non-Archimedean local field, with an emphasis on regularity properties of functions with finite variation, and on…

Number Theory · Mathematics 2022-03-16 Clayton Petsche , Naveen Somasunderam

Starting from a $D=3$, $N=4$ supersymmetric theory for matter fields, a twist with a Grassmann parity change is defined which maps the theory into a gauge fixed, abelian $BF$ theory on curved 3-manifolds. After adding surface terms to this…

High Energy Physics - Theory · Physics 2009-10-22 R. Brooks , J. -G. Demers , C. Lucchesi

The symmetric Nonnegative Matrix Factorization (NMF), a special but important class of the general NMF, has found numerous applications in data analysis such as various clustering tasks. Unfortunately, designing fast algorithms for the…

Machine Learning · Computer Science 2023-01-26 Xiao Li , Zhihui Zhu , Qiuwei Li , Kai Liu

In this paper, we discuss the problem of minimizing the sum of two convex functions: a smooth function plus a non-smooth function. Further, the smooth part can be expressed by the average of a large number of smooth component functions, and…

Machine Learning · Computer Science 2016-11-17 Luo Luo , Zihao Chen , Zhihua Zhang , Wu-Jun Li

We define discrete nested sums over integer points for symbols on the real line, which obey stuffle relations whenever they converge. They relate to Chen integrals of symbols via the Euler-MacLaurin formula. Using a suitable holomorphic…

Number Theory · Mathematics 2009-12-11 Dominique Manchon , Sylvie Paycha

The probabilistic bisection algorithm (PBA) solves a class of stochastic root-finding problems in one dimension by successively updating a prior belief on the location of the root based on noisy responses to queries at chosen points. The…

Probability · Mathematics 2016-12-14 Peter I. Frazier , Shane G. Henderson , Rolf Waeber