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In this paper, we study the general problem of optimizing a convex function $F(L)$ over the set of $p \times p$ matrices, subject to rank constraints on $L$. However, existing first-order methods for solving such problems either are too…

Machine Learning · Statistics 2017-12-12 Mohammadreza Soltani , Chinmay Hegde

A sharp explicit estimate is proved for the difference $e^\beta-\alpha$ when $\alpha$ and $\beta$ are nonzero algebraic numbers.

Number Theory · Mathematics 2007-05-23 Yu. Nesterenko , M. Waldschmidt

Approximate Bayesian computation (ABC) is a set of techniques for Bayesian inference when the likelihood is intractable but sampling from the model is possible. This work presents a simple yet effective ABC algorithm based on the…

Computation · Statistics 2019-03-01 Yanzhi Chen , Michael U. Gutmann

Some fractional Newton methods have been proposed in order to find roots of nonlinear equations using fractional derivatives. In this paper we introduce a fractional Newton method with order $\alpha+1$ and compare with another fractional…

Numerical Analysis · Mathematics 2019-09-20 Giro Candelario , Alicia Cordero , Juan R. Torregrosa

Let $f$ be an $E$-function (in Siegel's sense) not of the form $e^{\beta z}$, $\beta \in \overline{\mathbb{Q}}$, and let $\log$ denote any fixed determination of the complex logarithm. We first prove that there exists a finite set $S(f)$…

Number Theory · Mathematics 2024-09-30 Stéphane Fischler , Tanguy Rivoal

It is a consequence of existing literature that least and greatest fixed-points of monotone polynomials on Heyting algebras-that is, the algebraic models of the Intuitionistic Propositional Calculus-always exist, even when these algebras…

Logic in Computer Science · Computer Science 2016-01-05 Silvio Ghilardi , Maria Joao Gouveia , Luigi Santocanale

We present a new algorithm for approximate inference in probabilistic programs, based on a stochastic gradient for variational programs. This method is efficient without restrictions on the probabilistic program; it is particularly…

Machine Learning · Statistics 2013-01-08 David Wingate , Theophane Weber

We obtain matching direct and inverse theorems for the degree of weighted $L_p$-approximation by polynomials with the Jacobi weights $(1-x)^\alpha (1+x)^\beta$. Combined, the estimates yield a constructive characterization of various…

Classical Analysis and ODEs · Mathematics 2017-10-17 Kirill A. Kopotun , Dany Leviatan , Igor A. Shevchuk

Derivative-based algorithms are ubiquitous in statistics, machine learning, and applied mathematics. Automatic differentiation offers an algorithmic way to efficiently evaluate these derivatives from computer programs that execute relevant…

Computation · Statistics 2022-03-01 Charles C. Margossian , Michael Betancourt

Holomorphic functions are amazing because their values in an ever so small disk in the complex plane completely determine the function values at arbitrary points in their maximum possible domain. The process of extending such a function…

Complex Variables · Mathematics 2015-05-15 Stefan Kranich

We study approximation by arbitrary linear combinations of $n$ translates of a single function of periodic functions. We construct some methods of this approximation for functions in a class induced by the convolution with a given function,…

Numerical Analysis · Mathematics 2017-03-01 Dinh Dũng , Charles A. Micchelli , Vu Nhat Huy

We investigate the problem of approximating the matrix function $f(A)$ by $r(A)$, with $f$ a Markov function, $r$ a rational interpolant of $f$, and $A$ a symmetric Toeplitz matrix. In a first step, we obtain a new upper bound for the…

Numerical Analysis · Mathematics 2022-01-19 Bernhard Beckermann , Joanna Bisch , Robert Luce

Motivated by the conspicuous use of momentum-based algorithms in deep learning, we study a nonsmooth nonconvex stochastic heavy ball method and show its convergence. Our approach builds upon semialgebraic (definable) assumptions commonly…

Optimization and Control · Mathematics 2024-01-24 Tam Le

We introduce Flat Hilbert Bayesian Inference (FHBI), an algorithm designed to enhance generalization in Bayesian inference. Our approach involves an iterative two-step procedure with an adversarial functional perturbation step and a…

Machine Learning · Computer Science 2025-06-10 Tuan Truong , Quyen Tran , Quan Pham-Ngoc , Nhat Ho , Dinh Phung , Trung Le

Purpose of writing this paper is to solve a transcendental function containing a product of a variable and its double exponential by a unique method of approximation. If the value of the said product is given, then its inverse function is…

Numerical Analysis · Mathematics 2025-11-25 Narinder Kumar Wadhawan

We consider optimization of composite objective functions, i.e., of the form $f(x)=g(h(x))$, where $h$ is a black-box derivative-free expensive-to-evaluate function with vector-valued outputs, and $g$ is a cheap-to-evaluate real-valued…

Machine Learning · Statistics 2019-06-05 Raul Astudillo , Peter I. Frazier

We present a complete algorithm for finding an exact minimal polynomial from its approximate value by using an improved parameterized integer relation construction method. Our result is superior to the existence of error controlling on…

Symbolic Computation · Computer Science 2010-01-06 Xiaolin Qin , Yong Feng , Jingwei Chen , Jingzhong Zhang

We demonstrate that a modification of the classical index calculus algorithm can be used to factor integers. More generally, we reduce the factoring problem to finding an overdetermined system of multiplicative relations in any factor base…

Number Theory · Mathematics 2023-07-21 Katherine E. Stange

The goal of this notice is to present a proof of Bachet's conjecture based exclusively on the fundamental theorem of arithmetic. The novelty of this proof consists in its introduction of a partial order on rational integers through the…

Number Theory · Mathematics 2013-10-22 Felix Sidokhine

In this report, a novel approach to intelligence and learning is introduced, this approach is based on what we call 'perception logic'. Based on this logic, a computing mechanism and automata are introduced. Multi-resolution analysis of…

Artificial Intelligence · Computer Science 2007-05-23 Mohamed A. Belal