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This set of Montreal lectures is an elementary and sketchy introduction to the general field of random matrices. The first half is devoted to combinatorial models, whereas the second half deals with random matrix questions(GUE, etc...).

Probability · Mathematics 2007-12-27 Pierre van Moerbeke

Our introductory classes in statistics and data science use too much mathematics. The key causal effect which our students want our classes to have is to improve their future performance and opportunities. The more professional their…

Other Statistics · Statistics 2020-12-29 David Kane

This is an extended and corrected version of lecture notes originally written for a one semester course at Leibniz University Hannover. The main aim of the notes is to give an introduction to the mathematical methods used in describing…

Mathematical Physics · Physics 2017-04-20 Pieter Naaijkens

These notes are based on lecture courses I gave to third year mathematics students at Cambridge. They could form a basis of an elementary one--term lecture course on integrable systems covering the Arnold-Liouville theorem, inverse…

High Energy Physics - Theory · Physics 2026-01-13 Maciej Dunajski

An introductory overview of vector spaces, algebras, and linear geometries over an arbitrary commutative field is given. Quotient spaces are emphasized and used in constructing the exterior and the symmetric algebras of a vector space.…

History and Overview · Mathematics 2011-10-18 Richard A. Smith

This introduction begins with a section on fundamental notions of mathematical logic, including propositional logic, predicate or first-order logic, completeness, compactness, the L\"owenheim-Skolem theorem, Craig interpolation, Beth's…

Logic · Mathematics 2023-11-28 Anton Freund

I developed the lecture notes based on my ``Linear Model'' course at the University of California, Berkeley over the past ten years. This book provides an intermediate-level introduction to the linear model. It balances rigorous proofs and…

Methodology · Statistics 2025-06-23 Peng Ding

Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).

Machine Learning · Computer Science 2009-04-24 Amnon Shashua

These lecture notes accompany a one-semester graduate course on information and learning in economic theory. Topics include common knowledge, Bayesian updating, monotone-likelihood ratio properties, affiliation, the Blackwell order, cost of…

Theoretical Economics · Economics 2023-05-22 Annie Liang

This article serves as the regression analysis lecture notes in the Intelligent Computing course cluster (including the courses of Artificial Intelligence, Data Mining, Machine Learning, and Pattern Recognition). It aims to provide students…

Machine Learning · Computer Science 2025-12-05 Jingyuan Wang , Jiahao Ji

Mathematical concepts and tools have shaped the field of visualization in fundamental ways and played a key role in the development of a large variety of visualization techniques. In this chapter, we sample the visualization literature to…

Human-Computer Interaction · Computer Science 2019-09-12 Ingrid Hotz , Roxana Bujack , Christoph Garth , Bei Wang

A short introduction to the mathematical methods and technics of differential algebras and modules adapted to the problems of mathematical and theoretical physics is presented.

Rings and Algebras · Mathematics 2018-08-29 Victor Zharinov

The aim of this chapter is to identify and characterise the pedagogical model prescribed for this particular mathematics teaching delivered in post-primary vocational training. More specifically, the contribution investigates two major…

History and Overview · Mathematics 2023-08-01 Xavier Sido

The main purpose of this book is to propose an introduction to the modern tools of algebraic complexity. To remain as simple as possible while providing meaningful examples, we chose to focus on effective linear algebra; this is certainly…

Commutative Algebra · Mathematics 2016-04-05 Jounaïdi Abdeljaoued , Henri Lombardi

This is a set of lecture notes used in a graduate topic class in applied mathematics called ``Quantum Algorithms for Scientific Computation'' at the Department of Mathematics, UC Berkeley during the fall semester of 2021. These lecture…

Quantum Physics · Physics 2022-01-21 Lin Lin

In this paper we present our experience in using visualization in mathematics education. The experience with our university courses: "Computer tools in matematics" and "Symbolic algebra" provides the basis for mathematics teacher education…

Computers and Society · Computer Science 2019-10-15 Branko Malesevic , Ivana Jovovic , Bojan Banjac

This document presents a series of open questions arising in matrix computations, i.e., the numerical solution of linear algebra problems. It is a result of working groups at the workshop Linear Systems and Eigenvalue Problems, which was…

Over the past thirty years or so the authors have been teaching various programming for mathematics courses at our respective Universities, as well as incorporating computer algebra and numerical computation into traditional mathematics…

History and Overview · Mathematics 2022-03-16 Jack Betteridge , Eunice Y. S. Chan , Robert M. Corless , James H. Davenport , James Grant

Basic principles of mathematical modeling are reviewed in this book, with the focus on physics and its practical applications, and examples of selected mathematical methods are presented. Most of the models have been imported from physics…

Classical Physics · Physics 2025-07-14 Sergej Pankratow

In these lecture notes, we give a brief introduction to some elements of category theory. The choice of topics is guided by applications to functional programming. Firstly, we study initial algebras, which provide a mathematical…

Programming Languages · Computer Science 2026-03-09 Benedikt Ahrens , Kobe Wullaert