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System modeling is a classical approach to ensure their reliability since it is suitable both for a formal verification and for software testing techniques. In the context of model-based testing an approach combining random testing and…

Software Engineering · Computer Science 2018-06-14 Julien Bernard , Pierre-Cyrille Héam , Olga Kouchnarenko

Constructive methods for matrices of multihomogeneous (or multigraded) resultants for unmixed systems have been studied by Weyman, Zelevinsky, Sturmfels, Dickenstein and Emiris. We generalize these constructions to mixed systems, whose…

Symbolic Computation · Computer Science 2010-02-03 Ioannis Z. Emiris , Angelos Mantzaflaris

Totally symmetric self-complementary plane partitions (TSSCPPs) are boxed plane partitions with the maximum possible symmetry. We use the well-known representation of TSSCPPs as a dimer model on a honeycomb graph enclosed in one-twelfth of…

Probability · Mathematics 2021-11-01 Arvind Ayyer , Sunil Chhita

We develop several efficient algorithms for the classical \emph{Matrix Scaling} problem, which is used in many diverse areas, from preconditioning linear systems to approximation of the permanent. On an input $n\times n$ matrix $A$, this…

Data Structures and Algorithms · Computer Science 2017-04-10 Zeyuan Allen-Zhu , Yuanzhi Li , Rafael Oliveira , Avi Wigderson

We introduce the concept of matrix liberation process, a random matrix counterpart of the liberation process in free probability, and prove a large deviation upper bound for its empirical distribution with several properties on its rate…

Probability · Mathematics 2019-05-21 Yoshimichi Ueda

A model of multicellular systems with several types of cells is developed from the phase field model. The model is presented as a set of partial differential equations of the field variables, each of which expresses the shape of one cell.…

Biological Physics · Physics 2015-05-30 Makiko Nonomura

This chapter is an introduction to the connection between random matrices and maps, i.e graphs drawn on surfaces. We concentrate on the one-matrix model and explain how it encodes and allows to solve a map enumeration problem.

Mathematical Physics · Physics 2011-04-18 J. Bouttier

We are concerned with an approximation problem for a symmetric positive semidefinite matrix due to motivation from a class of nonlinear machine learning methods. We discuss an approximation approach that we call {matrix ridge…

Machine Learning · Statistics 2013-12-18 Zhihua Zhang

The steady-state currents and densities of a one-dimensional totally asymmetric exclusion process (TASEP) with particles that occlude an integer number ($d$) of lattice sites are computed using various mean field approximations and Monte…

Statistical Mechanics · Physics 2007-05-23 G. W. Lakatos , T. Chou

We present an exact solution of a probabilistic cellular automaton for traffic with open boundary conditions, e.g. cars can enter and leave a part of a highway with certain probabilities. The model studied is the asymmetric exclusion…

Statistical Mechanics · Physics 2015-06-25 M. R. Evans , N. Rajewsky , E. R. Speer

We consider the problem of solving TAP mean field equations by iteration for Ising model with coupling matrices that are drawn at random from general invariant ensembles. We develop an analysis of iterative algorithms using a dynamical…

Disordered Systems and Neural Networks · Physics 2016-04-06 Manfred Opper , Burak Çakmak , Ole Winther

In science and engineering, intelligent processing of complex signals such as images, sound or language is often performed by a parameterized hierarchy of nonlinear processing layers, sometimes biologically inspired. Hierarchical systems…

Machine Learning · Computer Science 2012-12-27 Miguel Á. Carreira-Perpiñán , Weiran Wang

We study the asymptotic behaviour of the trace (the sum of the diagonal parts) of a plane partition of the positive integer n, assuming that this parfition is chosen uniformly at random from the set of all such partitions.

Combinatorics · Mathematics 2011-11-10 Ljuben Mutafchiev , Emil Kamenov

This paper addresses the general problem of modelling and learning rank data with ties. We propose a probabilistic generative model, that models the process as permutations over partitions. This results in super-exponential combinatorial…

Information Retrieval · Computer Science 2010-10-05 Tran The Truyen , Dinh Q. Phung , Svetha Venkatesh

In this work we use matrix models to study the problem of strength distributions. This is motivated by noticing near exponential fall offs of strengths in calculated magnetic dipole excitations. We emphasize that the quality of the…

Nuclear Theory · Physics 2021-04-27 Larry Zamick , Arun Kingan

The totally asymmetric simple exclusion process with generalized update is a version of the discrete time totally asymmetric exclusion process with an additional inter-particle interaction that controls the degree of particle clustering.…

Statistical Mechanics · Physics 2024-03-21 Nadezhda Zh Bunzarova , Nina C Pesheva , Alexander M Povolotsky

Generalized planning accelerates classical planning by finding an algorithm-like policy that solves multiple instances of a task. A generalized plan can be learned from a few training examples and applied to an entire domain of problems.…

Robotics · Computer Science 2021-09-24 Aidan Curtis , Tom Silver , Joshua B. Tenenbaum , Tomas Lozano-Perez , Leslie Pack Kaelbling

Cell size control and homeostasis is a major topic in cell biology yet to be fully understood. Several growth laws like the timer, adder, and sizer were proposed, and mathematical approaches that model cell growth and division were…

Cell Behavior · Quantitative Biology 2023-07-19 Aviv Arcobi , Stanislav Burov

A new technique for approximating the entire solution set for a nonlinear system of relations (nonlinear equations, inequalities, etc. involving algebraic, smooth, or even continuous functions) is presented. The technique is to first plot…

Numerical Analysis · Computer Science 2017-12-07 David I. Spivak

A density matrix describes the statistical state of a quantum system. It is a powerful formalism to represent both the quantum and classical uncertainty of quantum systems and to express different statistical operations such as measurement,…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Alejandro Gallego , Santiago Toledo-Cortés , Vladimir Vargas-Calderón