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Estimating mutual information between continuous random variables is often intractable and extremely challenging for high-dimensional data. Recent progress has leveraged neural networks to optimize variational lower bounds on mutual…

Machine Learning · Computer Science 2020-12-01 Ruizhi Liao , Daniel Moyer , Polina Golland , William M. Wells

Certain quantum topological invariants of three manifolds can be written in the form of the Gaussian sum. It is shown that such topological invariants can be approximated efficiently by a quantum computer. The invariants discussed here are…

Quantum Physics · Physics 2009-03-11 K. Shiokawa

We look at explicit ways to bring one or two antiunitary symmetries into a standard form via unitary conjugation. We carefully reproduce Wigner's proof in two special cases, where the antiunitary operators square to $+I$, or to $-I$.…

Mathematical Physics · Physics 2025-08-22 Terry A. Loring

Polynomial multiplication is a fundamental problem in symbolic computation. There are efficient methods for the multiplication of two univariate polynomials. However, there is rarely efficiently nontrivial method for the multiplication of…

Computational Complexity · Computer Science 2024-03-20 Cancan Wang , Ming Su , Gang Wang , Qingpo Zhang

Motivated by an ongoing project on computer aided derivation of asymptotic models governed by partial differential equations, we introduce a class of term transformations that consists of traversal strategies and insertion of contexts. We…

Logic in Computer Science · Computer Science 2021-12-15 Walid Belkhir , Nicolas Ratier , Duy Duc Nguyen , Michel Lenczner

The term UniMath refers both to a formal system for mathematics, as well as a computer-checked library of mathematics formalized in that system. The UniMath system is a core dependent type theory, augmented by the univalence axiom. The…

Logic in Computer Science · Computer Science 2019-07-16 Benedikt Ahrens , Ralph Matthes , Anders Mörtberg

This work represents a natural coalescence of two important lines of work: learning mixtures of Gaussians and algorithmic robust statistics. In particular we give the first provably robust algorithm for learning mixtures of any constant…

Data Structures and Algorithms · Computer Science 2021-07-27 Allen Liu , Ankur Moitra

This paper investigates solving convex composite optimization on an undirected network, where each node, privately endowed with a smooth component function and a nonsmooth one, is required to minimize the sum of all the component functions…

Optimization and Control · Mathematics 2021-08-13 Xuyang Wu , Jie Lu

After a historical discussion of classical uniformisation results for Riemann surfaces, of problems appearing in higher dimensions, and of uniformisation results for projective manifolds with trivial or ample canonical bundle, we introduce…

Algebraic Geometry · Mathematics 2019-02-22 Daniel Greb , Stefan Kebekus , Behrouz Taji

This work explores the tensor and combinatorial constructs underlying the linearised higher-order variational equations of a generic autonomous system along a particular solution. The main result of this paper is a compact yet explicit and…

Exactly Solvable and Integrable Systems · Physics 2015-02-11 Sergi Simon

Unitary equivariance is a natural symmetry that occurs in many contexts in physics and mathematics. Optimization problems with such symmetry can often be formulated as semidefinite programs for a $d^{p+q}$-dimensional matrix variable that…

Quantum Physics · Physics 2025-01-07 Dmitry Grinko , Maris Ozols

The Conjugate Gradient method (CGM) is known to be the fastest generic iterative method for solving linear systems with symmetric sign definite matrices. In this paper, we modify this method so that it could find fundamental solitary waves…

Pattern Formation and Solitons · Physics 2015-05-13 Taras I. Lakoba

The binary Euclidean algorithm is a variant of the classical Euclidean algorithm. It avoids multiplications and divisions, except by powers of two, so is potentially faster than the classical algorithm on a binary machine. We describe the…

Data Structures and Algorithms · Computer Science 2013-03-13 Richard P. Brent

In this paper, calculus of variation methods are generalized to find min-max optimal solution of uncertain dynamical systems with uncertain or certain cost. First, a new form of Euler-Lagrange conditions for uncertain systems is presented.…

Optimization and Control · Mathematics 2013-05-28 Farid Sheikholeslam , R. Doosthoseyni

The Stochastic Extragradient (SEG) method is one of the most popular algorithms for solving min-max optimization and variational inequalities problems (VIP) appearing in various machine learning tasks. However, several important questions…

Optimization and Control · Mathematics 2022-02-23 Eduard Gorbunov , Hugo Berard , Gauthier Gidel , Nicolas Loizou

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result. The output allows…

Machine Learning · Computer Science 2024-07-17 Roberto Esposito , Mattia Cerrato , Marco Locatelli

Many language generation models are now available for a wide range of generation tasks, including machine translation and summarization. Combining such diverse models may lead to further progress, but ensembling generation models is…

Computation and Language · Computer Science 2022-10-31 Jungo Kasai , Keisuke Sakaguchi , Ronan Le Bras , Hao Peng , Ximing Lu , Dragomir Radev , Yejin Choi , Noah A. Smith

The unification problem in a propositional logic is to determine, given a formula F, whether there exists a substitution s such that s(F) is in that logic. In that case, s is a unifier of F. When a unifiable formula has minimal complete…

Logic in Computer Science · Computer Science 2020-04-20 Philippe Balbiani , Çiğdem Gencer , Maryam Rostamigiv , Tinko Tinchev

We study the problem of detecting outlier pairs of strongly correlated variables among a collection of $n$ variables with otherwise weak pairwise correlations. After normalization, this task amounts to the geometric task where we are given…

Data Structures and Algorithms · Computer Science 2018-01-08 Matti Karppa , Petteri Kaski , Jukka Kohonen

It is the aim of this work to identify and illustrate the potential and weaknesses of the computer algebra system Maple in the area of the Calculus of Variations: a classical area of mathematics that studies the methods for finding maximum…

Optimization and Control · Mathematics 2008-11-26 Andreia M. F. Louro , Delfim F. M. Torres