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We outline basic principles of a new method that gives a conceptual reasoning for and, at the same time, proofs of (super)congruences for truncated sums of arithmetic hypergeometric evaluations.

Number Theory · Mathematics 2020-09-24 Wadim Zudilin

We propose the first non-trivial generic decoding algorithm for codes in the sum-rank metric. The new method combines ideas of well-known generic decoders in the Hamming and rank metric. For the same code parameters and number of errors,…

Information Theory · Computer Science 2021-10-29 Sven Puchinger , Julian Renner , Johan Rosenkilde

This paper proposes a Perturbed Proximal Gradient ADMM (PPG-ADMM) framework for solving general nonconvex composite optimization problems, where the objective function consists of a smooth nonconvex term and a nonsmooth weakly convex term…

Optimization and Control · Mathematics 2026-01-06 Yuan Zhou , Xinli Shi , Luyao Guo , Jinde Cao , Mahmoud Abdel-Aty

We propose an adaptive smoothing algorithm based on Nesterov's smoothing technique in \cite{Nesterov2005c} for solving "fully" nonsmooth composite convex optimization problems. Our method combines both Nesterov's accelerated proximal…

Optimization and Control · Mathematics 2016-07-05 Quoc Tran-Dinh

This paper presents two new augmented flexible (AF)-Krylov subspace methods, AF-GMRES and AF-LSQR, to compute solutions of large-scale linear discrete ill-posed problems that can be modeled as the sum of two independent random variables,…

Numerical Analysis · Mathematics 2023-10-10 Malena Sabate Landman , Jiahua Jiang , Jianru Zhang , Wuwei Ren

In this paper, we develop a splitting algorithm incorporating Bregman distances to solve a broad class of linearly constrained composite optimization problems, whose objective function is the separable sum of possibly nonconvex nonsmooth…

Optimization and Control · Mathematics 2024-10-01 Tan Nhat Pham , Minh N. Dao , Andrew Eberhard , Nargiz Sultanova

A summation framework is developed that enhances Karr's difference field approach. It covers not only indefinite nested sums and products in terms of transcendental extensions, but it can treat, e.g., nested products defined over roots of…

Symbolic Computation · Computer Science 2015-02-04 Carsten Schneider

We present an algorithm for low rank decomposition of tensors of any symmetry type, from fully asymmetric to fully symmetric. It recovers the decomposition one summand at a time via the higher-order power method. This approach is known to…

Numerical Analysis · Mathematics 2026-05-22 Kexin Wang , João M. Pereira , Joe Kileel , Anna Seigal

We propose a new method for unconstrained optimization of a smooth and strongly convex function, which attains the optimal rate of convergence of Nesterov's accelerated gradient descent. The new algorithm has a simple geometric…

Optimization and Control · Mathematics 2015-06-30 Sébastien Bubeck , Yin Tat Lee , Mohit Singh

Given two polynomials, we find a convergence property of the GCD of the rising factorial and the falling factorial. Based on this property, we present a unified approach to computing the universal denominators as given by Gosper's algorithm…

Classical Analysis and ODEs · Mathematics 2007-11-22 William Y. C. Chen , Peter Paule , Husam L. Saad

An elementary proof is given for a nonterminating "strange" cubic $_7F_6$-series summation formula of Gasper and Rahman, through the modified Abel lemma on summation by parts. As a byproduct, an interesting nonterminating…

Classical Analysis and ODEs · Mathematics 2015-04-27 Chenying Wang , Xiaojing Chen

We present a new accelerated stochastic second-order method that is robust to both gradient and Hessian inexactness, which occurs typically in machine learning. We establish theoretical lower bounds and prove that our algorithm achieves…

Optimization and Control · Mathematics 2024-05-28 Artem Agafonov , Dmitry Kamzolov , Alexander Gasnikov , Ali Kavis , Kimon Antonakopoulos , Volkan Cevher , Martin Takáč

We propose sparseGeoHOPCA, a novel framework for sparse higher-order principal component analysis (SHOPCA) that introduces a geometric perspective to high-dimensional tensor decomposition. By unfolding the input tensor along each mode and…

Numerical Analysis · Mathematics 2025-06-11 Renjie Xu , Chong Wu , Maolin Che , Zhuoheng Ran , Yimin Wei , Hong Yan

In this paper, we obtain analytical solutions of Laplace transform based some generalized class of the hyperbolic integrals in terms of hypergeometric functions ${}_3F_2 (\pm1)$, ${}_4F_3 (\pm1)$, ${}_5F_4(\pm1)$, ${}_6F_5(\pm1)$,…

Classical Analysis and ODEs · Mathematics 2018-08-21 M. I. Qureshi , Showkat Ahmad Dar

In recent years, Z.-W. Sun proposed several sophisticated conjectures on congruences for finite sums with terms involving combinatorial sequences such as central trinomial coefficients, Domb numbers and Franel numbers. These sums are double…

Number Theory · Mathematics 2017-11-28 Yan-Ping Mu , Zhi-Wei Sun

We consider the problem of decomposing a real-valued symmetric tensor as the sum of outer products of real-valued vectors. Algebraic methods exist for computing complex-valued decompositions of symmetric tensors, but here we focus on…

Numerical Analysis · Mathematics 2018-08-23 Tamara G. Kolda

Abramov's algorithm enables us to decide whether a univariate rational function can be written as a difference of another rational function, which has been a fundamental algorithm for rational summation. In 2014, Chen and Singer generalized…

Symbolic Computation · Computer Science 2017-06-29 Shaoshi Chen

We present an algebraic framework to represent indefinite nested sums over hypergeometric expressions in difference rings. In order to accomplish this task, parts of Karr's difference field theory have been extended to a ring theory in…

Symbolic Computation · Computer Science 2015-03-24 Carsten Schneider

We derive a stronger uniqueness result if a function with compact support and its truncated Hilbert transform are known on the same interval by using the Sokhotski-Plemelj formulas. To find a function from its truncated Hilbert transform,…

Machine Learning · Computer Science 2020-02-13 Jason You

It has been shown numerically that the performance of the Levenberg-Marquardt algorithm can be improved by including a second order correction known as the geodesic acceleration. In this paper we give the method a more sound theoretical…

Optimization and Control · Mathematics 2012-07-23 Mark K. Transtrum , James P. Sethna