Convexity and The Principle of Duality
A gentle and visual introduction to the topic of Convex Optimization (part 2/3). In this video, we give the definition of convex sets, convex functions, and convex optimization problems. We also present a beautiful and extremely useful notion in convexity optimization, which is the princ
From playlist Convex Optimization
Solving an equation with variables on both side and one solution
👉 Learn how to solve multi-step equations with variable on both sides of the equation. An equation is a statement stating that two values are equal. A multi-step equation is an equation which can be solved by applying multiple steps of operations to get to the solution. To solve a multi-s
From playlist Solve Multi-Step Equations......Help!
Solving a multi-step equation by multiplying by the denominator
👉 Learn how to solve multi-step equations with variable on both sides of the equation. An equation is a statement stating that two values are equal. A multi-step equation is an equation which can be solved by applying multiple steps of operations to get to the solution. To solve a multi-s
From playlist How to Solve Multi Step Equations with Variables on Both Sides
In this video, I present a very classical example of a duality argument: Namely, I show that T^T is one-to-one if and only if T is onto and use that to show that T is one-to-one if and only if T^T is onto. This illustrates the beautiful interplay between a vector space and its dual space,
From playlist Dual Spaces
13_2 Optimization with Constraints
Here we use optimization with constraints put on a function whose minima or maxima we are seeking. This has practical value as can be seen by the examples used.
From playlist Advanced Calculus / Multivariable Calculus
Duality in Higher Categories-I by Pranav Pandit
PROGRAM DUALITIES IN TOPOLOGY AND ALGEBRA (ONLINE) ORGANIZERS: Samik Basu (ISI Kolkata, India), Anita Naolekar (ISI Bangalore, India) and Rekha Santhanam (IIT Mumbai, India) DATE & TIME: 01 February 2021 to 13 February 2021 VENUE: Online Duality phenomena are ubiquitous in mathematics
From playlist Dualities in Topology and Algebra (Online)
Duality in Algebraic Geometry by Suresh Nayak
PROGRAM DUALITIES IN TOPOLOGY AND ALGEBRA (ONLINE) ORGANIZERS: Samik Basu (ISI Kolkata, India), Anita Naolekar (ISI Bangalore, India) and Rekha Santhanam (IIT Mumbai, India) DATE & TIME: 01 February 2021 to 13 February 2021 VENUE: Online Duality phenomena are ubiquitous in mathematics
From playlist Dualities in Topology and Algebra (Online)
Xiaolu Tan: On the martingale optimal transport duality in the Skorokhod space
We study a martingale optimal transport problem in the Skorokhod space of cadlag paths, under finitely or infinitely many marginals constraint. To establish a general duality result, we utilize a Wasserstein type topology on the space of measures on the real value space, and the S-topology
From playlist HIM Lectures 2015
13_1 An Introduction to Optimization in Multivariable Functions
Optimization in multivariable functions: the calculation of critical points and identifying them as local or global extrema (minima or maxima).
From playlist Advanced Calculus / Multivariable Calculus
A very basic overview of optimization, why it's important, the role of modeling, and the basic anatomy of an optimization project.
From playlist Optimization
Lecture 9 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his lecture upon duality for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that arise in engineering.
From playlist Lecture Collection | Convex Optimization
Ivan Guo: Stochastic Optimal Transport in Financial Mathematics
Abstract: In recent years, the field of optimal transport has attracted the attention of many high-profile mathematicians with a wide range of applications. In this talk we will discuss some of its recent applications in financial mathematics, particularly on the problems of model calibra
From playlist SMRI Seminars
An introduction to the constrained optimization problems. Lagrangian, Lagrange multipliers, and Karush Kuhn Tucker conditions.
From playlist There and Back Again: A Tale of Slopes and Expectations (NeurIPS-2020 Tutorial)
Lecture 8 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, lectures on duality in the realm of electrical engineering and how it is utilized in convex optimization for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizi
From playlist Lecture Collection | Convex Optimization
Proofs & Goofs Ep1: Linear Programming #SoME2
Hey everybody! My name's Max Fishelson. I'm a CS theory PhD student at MIT. I like teaching math and singing songs. I hope you enjoy! maxkfish.com
From playlist Summer of Math Exposition 2 videos
The mother of all representer theorems for inverse problems & machine learning - Michael Unser
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai
From playlist Mathematics of data: Structured representations for sensing, approximation and learning
Lec 28 | MIT 18.086 Mathematical Methods for Engineers II
Linear Programming and Duality View the complete course at: http://ocw.mit.edu/18-086S06 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 18.086 Mathematical Methods for Engineers II, Spring '06
The Karush–Kuhn–Tucker (KKT) Conditions and the Interior Point Method for Convex Optimization
A gentle and visual introduction to the topic of Convex Optimization (part 3/3). In this video, we continue the discussion on the principle of duality, which ultimately leads us to the "interior point method" in optimization. Along the way, we derive the celebrated Karush–Kuhn–Tucker (KK
From playlist Convex Optimization
Solving a multi-step equation with fractions and variable on both sides
👉 Learn how to solve multi-step equations with variable on both sides of the equation. An equation is a statement stating that two values are equal. A multi-step equation is an equation which can be solved by applying multiple steps of operations to get to the solution. To solve a multi-s
From playlist How to Solve Multi Step Equations with Variables on Both Sides