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We introduce a new model of linear regression for random functional inputs taking into account the first order derivative of the data. We propose an estimation method which comes down to solving a special linear inverse problem. Our…

Statistics Theory · Mathematics 2016-08-16 André Mas , Besnik Pumo

A splitting scheme for backward doubly stochastic differential equations is proposed. The main idea is to decompose a backward doubly stochastic differential equation into a backward stochastic differential equation and a stochastic…

Numerical Analysis · Mathematics 2021-03-17 Feng Bao , Yanzhao Cao , He Zhang

The systems of nonlinear Volterra integral equations of the first kind with jump discontinuous kernels are studied. The iterative numerical method for such nonlinear systems is proposed. Proposed method employs the modified…

Numerical Analysis · Mathematics 2019-10-22 A. N. Tynda , D. N. Sidorov , N. A. Sidorov

This work wishes to support various mathematical issues concerning the iterative methods with the help of new programming languages. We consider a way to show how problems in math have an answer by using different academic resources and…

Mathematical Software · Computer Science 2009-05-29 Claudiu Chirilov

We perform certain alternating binomial summations with parameters that occur in the analysis of algorithms. A combination of integral and special function and special number representations is used. The results are sufficiently general to…

Mathematical Physics · Physics 2007-05-23 Mark W. Coffey

The problem of change-point estimation is considered under a general framework where the data are generated by unknown stationary ergodic process distributions. In this context, the consistent estimation of the number of change-points is…

Machine Learning · Statistics 2013-02-15 Azaden Khaleghi , Daniil Ryabko

This paper addresses the problem of checking invariant properties for a large class of symbolic transition systems, defined by a combination of SMT theories and quantifiers. State variables can be functions from an uninterpreted sort…

Logic in Computer Science · Computer Science 2024-03-01 Gianluca Redondi , Alessandro Cimatti , Alberto Griggio , Kenneth McMillan

Some iterative techniques are defined to solve reversible inverse problems and a common formulation is explained. Numerical improvements are suggested and tests validate the methods.

Optimization and Control · Mathematics 2011-12-06 Sébastien Marinesque

We begin by introducing the main ideas of the paper under discussion, and we give a brief description of the method proposed. Next, we discuss an alternative approach based on B-spline expansion, and lastly we make some comments on the…

Statistics Theory · Mathematics 2016-12-06 William Weimin Yoo

An application design is offered, which students of physics can use when authoring a solver for mechanical systems with constraints. A 'chainlist' concept is introduced to capture a constrained mechanical system configuration and to pass…

Physics Education · Physics 2015-03-17 Vladimir Vasilich Tregub

For a large class of systems of o.d.e.'s which have first integrals, the method of arrays yields the following results: i) The first integrals $I$ can be found by solving systems of linear equations. ii) How the first integral $I$ responds…

Mathematical Physics · Physics 2007-05-23 Lawrence Goldman

Sequentially solving similar optimization problems under strict runtime constraints is essential for many applications, such as robot control, autonomous driving, and portfolio management. The performance of local optimization methods in…

Machine Learning · Computer Science 2025-02-04 Elad Sharony , Heng Yang , Tong Che , Marco Pavone , Shie Mannor , Peter Karkus

A new approach is discussed for solving large nonsymmetric systems of linear equations with multiple right-hand sides. The first system is solved with a deflated GMRES method that generates eigenvector information at the same time that the…

Mathematical Physics · Physics 2007-07-05 Ronald B. Morgan , Walter Wilcox

We consider a general statistical linear inverse problem, where the solution is represented via a known (possibly overcomplete) dictionary that allows its sparse representation. We propose two different approaches. A model selection…

Methodology · Statistics 2017-10-31 Felix Abramovich , Daniela De Canditiis , Marianna Pensky

The paper briefly introduces multiple classifier systems and describes a new algorithm, which improves classification accuracy by means of recommendation of a proper algorithm to an object classification. This recommendation is done…

Information Retrieval · Computer Science 2015-04-22 Yury Kashnitsky , Dmitry I. Ignatov

A change point problem occurs in many statistical applications. If there exist change points in a model, it is harmful to make a statistical analysis without any consideration of the existence of the change points and the results derived…

Methodology · Statistics 2011-01-24 Xiaoping Shi , Yuehua Wu , Baisuo Jin

We take some first steps in providing a synthetic theory of distributions. In particular, we are interested in the use of distribution theory as foundation, not just as tool, in the study of the wave equation.

Category Theory · Mathematics 2007-05-23 Anders Kock , Gonzalo E. Reyes

We give an algorithm to compute the series expansion for the inverse of a given function. The algorithm is extremely easy to implement and gives the first $N$ terms of the series. We show several examples of its application in calculating…

Classical Analysis and ODEs · Mathematics 2007-05-23 Diego Dominici

In this article we study a class of generalised linear systems of difference equations with given non-consistent initial conditions and infinite many solutions. We take into consideration the case that the coefficients are square constant…

Dynamical Systems · Mathematics 2016-12-14 Nicholas Apostolopoulos , Fernando Ortega , Grigoris Kalogeropoulos

This paper is concerned with the detection of multiple change-points in the joint distribution of independent categorical variables. The procedures introduced rely on model selection and are based on a penalized least-squares criterion.…

Statistics Theory · Mathematics 2008-01-08 Nathalie Akakpo