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It is declared that the aim of simplifying representations of coefficients of power series of classical statistical mechanics is to simplify a process of obtaining estimates of the coefficients using their simplified representations. The…

Mathematical Physics · Physics 2022-07-18 G. I. Kalmykov

Recently, a novel method based on coding partitions [1]-[4] has been used to derive power series expansions to previously intractable problems. In this method the coefficients at $k$ are determined by summing the contributions made by each…

Combinatorics · Mathematics 2012-03-23 Victor Kowalenko

This is a survey on the use of low-degree polynomials to predict and explain the apparent statistical-computational tradeoffs in a variety of average-case computational problems. In a nutshell, this framework measures the complexity of a…

Statistics Theory · Mathematics 2025-06-13 Alexander S. Wein

Linear recurrence equations with constant coefficients define the power series coefficients of rational functions. However, one usually prefers to have an explicit formula for the sequence of coefficients, provided that such a formula is…

Symbolic Computation · Computer Science 2022-07-05 Bertrand Teguia Tabuguia , Wolfram Koepf

In this work, we introduce metrics to evaluate the use of simplified time series in the context of interpretability of a TSC -- a Time Series Classifier. Such simplifications are important because time series data, in contrast to text and…

Machine Learning · Computer Science 2025-11-04 Brigt Håvardstun , Felix Marti-Perez , Cèsar Ferri , Jan Arne Telle

Cycle representatives of persistent homology classes can be used to provide descriptions of topological features in data. However, the non-uniqueness of these representatives creates ambiguity and can lead to many different interpretations…

Algebraic Topology · Mathematics 2021-10-19 Lu Li , Connor Thompson , Gregory Henselman-Petrusek , Chad Giusti , Lori Ziegelmeier

We introduce a notion of complexity of diagrams (and in particular of objects and morphisms) in an arbitrary category, as well as a notion of complexity of functors between categories equipped with complexity functions. We discuss several…

Category Theory · Mathematics 2020-07-01 Saugata Basu , M. Umut Isik

Based on the full similarity in algebraic properties and differentiation rules between quaternionic (H-) holomorphic and complex (C-) holomorphic functions, we assume that there exists one holistic notion of a holomorphic function that has…

Complex Variables · Mathematics 2024-08-01 Michael Parfenov

This paper studies the equivalence between generalized holomorphic functions (GHF) and complex analytic functions in the framework of Robinson-Colombeau generalized numbers. In every non-Archimedean ring, the use of ordinary series is…

Functional Analysis · Mathematics 2026-04-21 Sekar Nugraheni , Paolo Giordano

Collaborative Representation Classification (CRC) for face recognition attracts a lot attention recently due to its good recognition performance and fast speed. Compared to Sparse Representation Classification (SRC), CRC achieves a…

Computer Vision and Pattern Recognition · Computer Science 2015-07-30 Xiaochao Qu , Suah Kim , Run Cui , Hyoung Joong Kim

We propose a method to reduce the complexity of Generalized Linear Models in the presence of categorical predictors. The traditional one-hot encoding, where each category is represented by a dummy variable, can be wasteful, difficult to…

Machine Learning · Statistics 2021-10-20 Emilio Carrizosa , Marcela Galvis Restrepo , Dolores Romero Morales

The main purpose is to introduce the so-called bicomplex (bc)-frames which is a special extension to bicomplex infinite Hilbert spaces of the classical frames. The crucial result is the characterization of bc-frames in terms of their…

Functional Analysis · Mathematics 2020-01-22 Aiad El Gourari , Allal Ghanmi , Mohammed Souid El Ainin

Simplification of fractional powers of positive rational numbers and of sums, products and powers of such numbers is taught in beginning algebra. Such numbers can often be expressed in many ways, as this article discusses in some detail.…

Symbolic Computation · Computer Science 2013-02-12 Albert D. Rich , David R. Stoutemyer

Computational mechanics, an approach to structural complexity, defines a process's causal states and gives a procedure for finding them. We show that the causal-state representation--an $\epsilon$-machine--is the minimal one consistent with…

Statistical Mechanics · Physics 2022-02-17 Cosma Rohilla Shalizi , James P. Crutchfield

Homomorphisms between relational structures are not only fundamental mathematical objects, but are also of great importance in an applied computational context. Indeed, constraint satisfaction problems (CSPs), a wide class of algorithmic…

Computational Complexity · Computer Science 2011-05-23 Martin Grohe , Marc Thurley

The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly simplifies the development of automatic tools for the analysis of biological systems.…

Computational Engineering, Finance, and Science · Computer Science 2010-06-29 Mario Coppo , Ferruccio Damiani , Maurizio Drocco , Elena Grassi , Angelo Troina

This paper compares Bayesian and classical feature ranking methods for interpretable fault diagnosis of brushless DC (BLDC) motors. Two Bayesian approaches, spike-and-slab and ARD logistic ranking, are evaluated against three classical…

Systems and Control · Electrical Eng. & Systems 2026-03-17 Waldemar Bauer , Jerzy Baranowski

Holonomic functions play an essential role in Computer Algebra since they allow the application of many symbolic algorithms. Among all algorithmic attempts to find formulas for power series, the holonomic property remains the most important…

Symbolic Computation · Computer Science 2022-04-18 Bertrand Teguia Tabuguia , Wolfram Koepf

A classification algorithm, called the Linear Centralization Classifier (LCC), is introduced. The algorithm seeks to find a transformation that best maps instances from the feature space to a space where they concentrate towards the center…

Machine Learning · Computer Science 2017-12-25 Mohammad Reza Bonyadi , Viktor Vegh , David C. Reutens

We propose a method for setting limits that avoids excluding parameter values for which the sensitivity falls below a specified threshold. These "power-constrained" limits (PCL) address the issue that motivated the widely used CLs…

Data Analysis, Statistics and Probability · Physics 2011-05-17 Glen Cowan , Kyle Cranmer , Eilam Gross , Ofer Vitells
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