Combinatorics | Mathematical proofs | Probabilistic arguments

Probabilistic method

The probabilistic method is a nonconstructive method, primarily used in combinatorics and pioneered by Paul Erdős, for proving the existence of a prescribed kind of mathematical object. It works by showing that if one randomly chooses objects from a specified class, the probability that the result is of the prescribed kind is strictly greater than zero. Although the proof uses probability, the final conclusion is determined for certain, without any possible error. This method has now been applied to other areas of mathematics such as number theory, linear algebra, and real analysis, as well as in computer science (e.g. randomized rounding), and information theory. (Wikipedia).

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Least squares method for simple linear regression

In this video I show you how to derive the equations for the coefficients of the simple linear regression line. The least squares method for the simple linear regression line, requires the calculation of the intercept and the slope, commonly written as beta-sub-zero and beta-sub-one. Deriv

From playlist Machine learning

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Logistic Regression

Overview of logistic regression, a statistical classification technique.

From playlist Machine Learning

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Linear regression

Linear regression is used to compare sets or pairs of numerical data points. We use it to find a correlation between variables.

From playlist Learning medical statistics with python and Jupyter notebooks

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Using a Multiplier to Solve the System of Equations Using Elimination

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

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Solving a System by Using a Multiplier for Elimination

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

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Labeling a System by Solving Using Elimination Method

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

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ML Tutorial: Probabilistic Numerical Methods (Jon Cockayne)

Machine Learning Tutorial at Imperial College London: Probabilistic Numerical Methods Jon Cockayne (University of Warwick) February 22, 2017

From playlist Machine Learning Tutorials

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Solving a system of equations with infinite many solutions

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

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Professor Mark Girolami: "Probabilistic Numerical Computation: A New Concept?"

The Turing Lectures: The Intersection of Mathematics, Statistics and Computation - Professor Mark Girolami: "Probabilistic Numerical Computation: A New Concept?" Click the below timestamps to navigate the video. 00:00:09 Introduction by Professor Jared Tanner 00:01:38 Profess

From playlist Turing Lectures

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Richard Lassaigne: Introduction à la théorie de la complexité

Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b

From playlist Mathematical Aspects of Computer Science

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Solve a System of Equations Using Elimination

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Hard

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Probability theory and AI | The Royal Society

Join Professor Zoubin Ghahramani to explore the foundations of probabilistic AI and how it relates to deep learning. 🔔Subscribe to our channel for exciting science videos and live events, many hosted by Brian Cox, our Professor for Public Engagement: https://bit.ly/3fQIFXB #Probability #A

From playlist Latest talks and lectures

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Probabilistic Numerics — moving BayesOpt expertise to the inner loop by Philipp Hennig

A Google TechTalk, presented by Philipp Hennig, 2022/02/08 ABSTRACT: BayesOpt Speaker Series. Bayesian Optimization experts are Gaussian process experts. And there is much more to do for Gaussian inference in the algorithmic space beyond outer-loop optimization. Using simulation — the solu

From playlist Google BayesOpt Speaker Series 2021-2022

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Fellow Short Talks: Dr Charles Sutton, Edinburgh University

Charles Sutton is a Reader (equivalent to Associate Professor: http://bit.ly/1W9UhqT) in Machine Learning at the University of Edinburgh. He has over 50 publications in a broad range of applications of probabilistic machine learning. His work in machine learning for software engineering ha

From playlist Short Talks

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Seminar In the Analysis and Methods of PDE (SIAM PDE): Andrea R. Nahmod

Title: Gibbs measures and propagation of randomness under the flow of nonlinear dispersive PDE Date: Thursday, May 5, 2022, 11:30 am EDT Speaker: Andrea R. Nahmod, University of Massachusetts Amherst The COVID-19 pandemic and consequent social distancing call for online venues of research

From playlist Seminar In the Analysis and Methods of PDE (SIAM PDE)

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Semantic models for higher-order Bayesian inference - Sam Staton, University of Oxford

In this talk I will discuss probabilistic programming as a method of Bayesian modelling and inference, with a focus on fully featured probabilistic programming languages with higher order functions, soft constraints, and continuous distributions. These languages are pushing the limits of e

From playlist Logic and learning workshop

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How to Solve a System of Equations Using Elimination

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

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Total Functions in the Polynomial Hierarchy - Robert Kleinberg

Computer Science/Discrete Mathematics Seminar I Topic: Total Functions in the Polynomial Hierarchy Speaker: Robert Kleinberg Affiliation: Cornell University Date: February 08, 2021 For more video please visit http://video.ias.edu

From playlist Mathematics

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PMSP - Computational pseudo-randomness and extractors II - Russell Impagliazzo

Russell Impagliazzo Institute for Advanced Study June 14, 2010 For more videos, visit http://video.ias.edu

From playlist Mathematics

Related pages

Ramsey's theorem | Linear algebra | Probability | Las Vegas algorithm | Combinatorics | Lovász local lemma | Chernoff bound | Information theory | Randomized rounding | Graph theory | Real analysis | Mathematics | Markov's inequality | Complete graph | Cycle (graph theory) | Exponential growth | Method of conditional probabilities | Number theory | Graph coloring | Independent set (graph theory) | Interactive proof system | Jiří Matoušek (mathematician) | Chromatic number | Random graph | Expected value | Random variable | Tournament (graph theory) | Paul Erdős