In quantum information theory, the idea of a typical subspace plays an important role in the proofs of many coding theorems (the most prominent example being ). Its role is analogous to that of the typical set in classical information theory. (Wikipedia).
Subspaces are the Natural Subsets of Linear Algebra | Definition + First Examples
A subspace is a subset that respects the two basic operations of linear algebra: vector addition and scalar multiplication. We say they are "closed under vector addition" and "closed under scalar multiplication". On a subspace, you can do linear algebra! Indeed, a subspace is an example of
From playlist Linear Algebra (Full Course)
From playlist Unlisted LA Videos
What's a subspace of a vector space? How do we check if a subset is a subspace?
From playlist Linear Algebra
A matrix of coefficients, when viewed in column form, is used to create a column space. This is simply the space created by a linear combination of the column vectors. A resulting vector, b, that does not lie in this space will not result in a solution to the linear system. A set of vec
From playlist Introducing linear algebra
Linear Algebra: What is a Subspace?
Learn the basics of Linear Algebra with this series from the Worldwide Center of Mathematics. Find more math tutoring and lecture videos on our channel or at http://centerofmath.org/
From playlist Basics: Linear Algebra
Classic linear algebra exercise: the union of a subspace is a subspace if and only if one is contained in the other. This is also good practice with the definition of a subspace, and also shows how to prove statements of the form p implies (q or r) Check out my vector space playlist: http
From playlist Vector Spaces
Examples of sets that are not subspaces and showing why they’re not subspaces Check out my Matrix Algebra playlist: https://www.youtube.com/playlist?list=PLJb1qAQIrmmAIZGo2l8SWvsHeeCLzamx0 Subscribe to my channel: https://www.youtube.com/channel/UCoOjTxz-u5zU0W38zMkQIFw
From playlist Matrix Algebra
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
Breakdown of time for each question Q1) 00:10 - 10:00 Q2) 10:05 - 19:40 Q3) 19:40 - 28:42 Q4) 29:00 - 34:45 Q5) 37:10 - 43:25 Q6) 43:40 - 49:20 Q7) 49:40 - 57:20 Q8) 58:10 - end
From playlist Tutorial 4
The Loss Landscape of Deep Neural Networks by Shankar Krishnan
DISCUSSION MEETING THE THEORETICAL BASIS OF MACHINE LEARNING (ML) ORGANIZERS: Chiranjib Bhattacharya, Sunita Sarawagi, Ravi Sundaram and SVN Vishwanathan DATE : 27 December 2018 to 29 December 2018 VENUE : Ramanujan Lecture Hall, ICTS, Bangalore ML (Machine Learning) has enjoyed tr
From playlist The Theoretical Basis of Machine Learning 2018 (ML)
Stefan Teufel: Peierls substitution for magnetic Bloch bands
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 SPECIAL 7th European congress of Mathematics Berlin 2016.
Robert Scheichl: Generalised finite elements: domain decomposition, optimal local approximation...
I will present an efficient implementation of the highly robust and scalable GenEO preconditioner in the high-performance PDE framework DUNE. The GenEO coarse space is constructed by combining low energy solutions of local generalised eigenproblems using a partition of unity. In this talk,
From playlist Numerical Analysis and Scientific Computing
Smooth Coverings of Space - Oded Regev
Computer Science/Discrete Mathematics Seminar I Topic: Smooth Coverings of Space Speaker: Oded Regev Affiliation: New York University Date: February 6, 2023 Let K be a convex body in Rn. In some cases (say when K is a cube), we can tile Rn using translates of K. However, in general (say
From playlist Mathematics
Simion Filip - Hypergeometric equations, Hodge theory, and Lyapunov exponents
Simion Filip Hypergeometric equations, Hodge theory, and Lyapunov exponents Ordinary differential equations in the complex plane is a classical topic that was related from the beginning with Hodge theory, i.e.the properties of holomorphic forms integrated over cycles on complex manifolds.
From playlist Maryland Analysis and Geometry Atelier
Linear Algebra - Lecture 27 - Subspaces of R^n
This video lecture contains definitions and examples of subspaces of R^n.
From playlist Linear Algebra Lectures
Roland Memisevic: "Multiview Feature Learning, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "Multiview Feature Learning, Pt. 2" Roland Memisevic, Johann Wolfgang Goethe-Universität Frankfurt Institute for Pure and Applied Mathematics, UCLA July 25, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-
From playlist GSS2012: Deep Learning, Feature Learning
Reduced-Order Modeling and Inversion for Large-Scale Problems of Geophysical Exploration
Date and Time: Thursday, May 12, 2022, 12:00pm Eastern time zone Speaker: Mikhail Zaslavsky, Schlumberger Doll Research Abstract: Geophysical exploration using electromagnetic and seismic method involves large-scale forward and nonlinear inverse problems that often have to be solved in re
From playlist SIAM Geosciences Webinar Series