Polynomial approximations -- Calculus II
This lecture is on Calculus II. It follows Part II of the book Calculus Illustrated by Peter Saveliev. The text of the book can be found at http://calculus123.com.
From playlist Calculus II
Linear Approximations and Differentials
Linear Approximation In this video, I explain the concept of a linear approximation, which is just a way of approximating a function of several variables by its tangent planes, and I illustrate this by approximating complicated numbers f without using a calculator. Enjoy! Subscribe to my
From playlist Partial Derivatives
Approximating Functions in a Metric Space
Approximations are common in many areas of mathematics from Taylor series to machine learning. In this video, we will define what is meant by a best approximation and prove that a best approximation exists in a metric space. Chapters 0:00 - Examples of Approximation 0:46 - Best Aproximati
From playlist Approximation Theory
Linear Algebra 6.6 Function Approximation; Fourier Series
My notes are available at http://asherbroberts.com/ (so you can write along with me). Elementary Linear Algebra: Applications Version 12th Edition by Howard Anton, Chris Rorres, and Anton Kaul A. Roberts is supported in part by the grants NSF CAREER 1653602 and NSF DMS 2153803.
From playlist Linear Algebra
Polynomial approximation of functions (part 1)
Using a polynomial to approximate a function at f(0). More free lessons at: http://www.khanacademy.org/video?v=sy132cgqaiU
From playlist Calculus
Linear Approximation & the Tangent Planes & the Differential: More Depth
Multivariable calculus lecture focusing on Linear Approximation & the Tangent Planes & the Differential
From playlist Multivariable Derivatives
Error bounds for Taylor approximations -- Calculus II
This lecture is on Calculus II. It follows Part II of the book Calculus Illustrated by Peter Saveliev. The text of the book can be found at http://calculus123.com.
From playlist Calculus II
Approximation & Estimation | Numbers | Maths | FuseSchool
An approximation is anything that is similar, but not exactly the same as something else. For example, if you were to say a 57 minute journey would take “about an hour”, you would be approximating. A value can be approximated by rounding, usually to a value that it is easier to work with
From playlist MATHS: Numbers
Minimax Approximation and the Exchange Algorithm
In this video we'll discuss minimax approximation. This is a method of approximating functions by minimisation of the infinity (uniform) norm. The exchange algorithm is an iterative method of finding the approximation which minimises the infinity norm. FAQ : How do you make these animatio
From playlist Approximation Theory
Anthony Nouy: Adaptive low-rank approximations for stochastic and parametric equations [...]
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 Numerical Analysis and Scientific Computing
Diego Mondéjar Ruiz (6/10/22): Approximation of compact metric spaces by finite samples
We address the problem of reconstructing topological properties of a compact metric space by means of simpler ones. In this context, we use inverse sequences of finite topological spaces and polyhedra made from finite approximations of the space. This construction is related with Borsuk's
From playlist Vietoris-Rips Seminar
Stability and sofic approximations for product groups and property (tau) - Adrian Ioana
Stability and Testability Topic: Stability and sofic approximations for product groups and property (tau) Speaker: Adrian Ioana Affiliation: University of California, San Diego Date: November 4, 2020 For more video please visit http://video.ias.edu
From playlist Stability and Testability
Nexus Trimester - Michael Kapralov (EPFL)
Approximating matchings in sublinear space Michael Kapralov (EPFL) March 08, 2016 Abstract: Finding maximum matchings in graphs is one of the most well-studied questions in combinatorial optimization. This problem is known to be solvable in polynomial time if the edge set of the graph can
From playlist 2016-T1 - Nexus of Information and Computation Theory - CEB Trimester
From playlist STAT 200 Video Lectures
A nearly optimal lower bound on the approximate degree of AC00- Mark Bun
Computer Science/Discrete Mathematics Seminar I Topic: A nearly optimal lower bound on the approximate degree of AC00 Speaker: A nearly optimal lower bound on the approximate degree of AC00 Speaker: Mark Bun Affiliation: Princeton University Date: October 23, 2017 For more videos, pleas
From playlist Mathematics
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention (AI Paper Explained)
#transformer #nystromer #nystromformer The Nyströmformer (or Nystromformer, Nyströmer, Nystromer), is a new drop-in replacement for approximating the Self-Attention matrix in Transformers with linear memory and time requirements. Most importantly, it uses the Nystrom-Method to subselect (
From playlist Papers Explained
DDPS | Distilling nonlinear shock waves
Classical reduced models rely on low-dimensional linear subspaces that are able to represent the solution manifold. For transport dominated problems, a suitable subspace does not exist, due to the slow decay in the Kolmogorov N-width of the solution manifold. In this talk, I will present d
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Mod-01 Lec-12 Solving ODE - BVPs Using Firute Difference Method
Advanced Numerical Analysis by Prof. Sachin C. Patwardhan,Department of Chemical Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Bombay: Advanced Numerical Analysis | CosmoLearning.org
Proving that orthogonal projections are a form of minimization
Description: Orthogonal projections provide the closest point on a subspace to some point off the subspace. We use Pythagoras to prove that this is always the case. Learning Objective: 1) Given a subspace and a point, compute the closest point in the subspace to the given point. This
From playlist Linear Algebra (Full Course)
Luis Scoccola (5/3/21): Approximate and discrete vector bundles
Synchronization problems, such as the problem of reconstructing a 3D shape from a set of 2D projections, can often be modeled by principal bundles. Similarly, the application of local PCA to a point cloud concentrated around a manifold approximates the tangent bundle of the manifold. In th
From playlist TDA: Tutte Institute & Western University - 2021