Linear programming relaxation

(ML 9.1) Linear regression - Nonlinearity via basis functions

Introduction to linear regression. Basis functions can be used to capture nonlinearities in the input variable. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA

From playlist Machine Learning

(ML 9.2) Linear regression - Definition & Motivation

Linear regression arises naturally from a sequence of simple choices: discriminative model, Gaussian distributions, and linear functions. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA

From playlist Machine Learning

Linear Programming (4)

Powered by https://www.numerise.com/ Formulating a linear programming problem

From playlist Linear Programming - Decision Maths 1

Linear Transformations and Linear Systems

In this video we discuss linear transformations. We start by examining the mathematical definition of a linear transformation and apply it to several examples including matrix multiplication and differentiation. We then see how linear transformations relate to linear systems (AKA linear

From playlist Linear Algebra

Intro to Linear Systems: 2 Equations, 2 Unknowns - Dr Chris Tisdell Live Stream

Free ebook http://tinyurl.com/EngMathYT Basic introduction to linear systems. We discuss the case with 2 equations and 2 unknowns. A linear system is a mathematical model of a system based on the use of a linear operator. Linear systems typically exhibit features and properties that ar

From playlist Intro to Linear Systems

What is a linear equation

👉 Learn about graphing linear equations. A linear equation is an equation whose highest exponent on its variable(s) is 1. i.e. linear equations has no exponents on their variables. The graph of a linear equation is a straight line. To graph a linear equation, we identify two values (x-valu

From playlist ⚡️Graph Linear Equations | Learn About

What is exactly an equation multiplier

👉 Learn all about the processes and definitions for solving linear equations. You will gain a better understanding about the vocabulary and steps used to solve liner equations such as how to isolate an equation and apply inverse operation using the property of equality. We will work step b

From playlist Solve Linear Equations | Learn About

Linear programming how to optimize the objective function

Learn how to solve problems using linear programming. A linear programming problem involves finding the maximum or minimum value of an equation, called the objective functions, subject to a system of inequalities, called the constraints. To solve a linear programming problem graphically,

From playlist Solve Linear Programming Problems #System

Approximating Max Cut with Subexponential Linear Programs - Tselil Schramm

Computer Science/Discrete Mathematics Seminar I Topic: Approximating Max Cut with Subexponential Linear Programs Speaker: Tselil Schramm Affiliation: Stanford University Date: March 29, 2021 For more video please visit http://video.ias.edu

From playlist Mathematics

Identifying Linear Functions

Define linear functions. Use function notation to evaluate linear functions. Learn to identify linear function from data, graphs, and equations.

From playlist Algebra 1

Zico Kolter: "Fast semidefinite programming for (differentiable) combinatorial optimization"

Deep Learning and Combinatorial Optimization 2021 "Fast semidefinite programming for (differentiable) combinatorial optimization" Zico Kolter - Carnegie Mellon University Institute for Pure and Applied Mathematics, UCLA February 25, 2021 For more information: https://www.ipam.ucla.edu/d

From playlist Deep Learning and Combinatorial Optimization 2021

A Non-equilibrium Bath in Theory and Experiment (Remote talk) by Matthias kruger

PROGRAM : FLUCTUATIONS IN NONEQUILIBRIUM SYSTEMS: THEORY AND APPLICATIONS ORGANIZERS : Urna Basu and Anupam Kundu DATE : 09 March 2020 to 19 March 2020 VENUE : Madhava Lecture Hall, ICTS, Bangalore THIS PROGRAM HAS BEEN MODIFIED ONLY FOR LOCAL (BANGALORE) PARTICIPANTS DUE TO COVID-19 RI

From playlist Fluctuations in Nonequilibrium Systems: Theory and Applications

A Framework for Quadratic Form Maximization over Convex Sets -Vijay Bhattiprolu

Computer Science/Discrete Mathematics Seminar II Topic: A Framework for Quadratic Form Maximization over Convex Sets Speaker: Vijay Bhattiprolu Affiliation: Member, School of Mathematics Date: April 28, 2020 For more video please visit http://video.ias.edu

From playlist Mathematics

Stanford Seminar - Recent progress in verifying neural networks, Zico Kolter

Zico Kolter, Associate Professor, Carnegie Mellon University May 4, 2022 This talk looks at the task of verifying deep networks, guaranteeing that outputs of a network obey certain properties for certain classes of inputs. Such approaches can be used to validate robustness and safety of

From playlist Stanford CS521 - AI Safety Seminar

An Isoperimetric Inequality for the Hamming Cube and Integrality Gaps in Graphs - Siavosh Benabbas

Siavosh Benabbas Institute for Advanced Study November 21, 2011 In 1970s Paul Erdos asked the following question: Consider all the boolean strings of length n. Assume that one has chosen a subset S of the strings such that no two chosen strings are different in precisely n/4 (or its closes

From playlist Mathematics

Optimisation: Linear Integer Programming - Professor Raphael Hauser

Bio Raphael Hauser studied Mathematics and Theoretical Physics at the EPFL and ETH in Lausanne and Zurich, Switzerland, followed by a PhD in Operations Research at Cornell University in Ithaca, USA. After a postdoc at Cambridge, Raphael joined the faculty at the University of Oxford, wher

From playlist Data science classes

Yunhao Tang: "Reinforcement Learning for Integer Programming: Learning to Cut"

Deep Learning and Combinatorial Optimization 2021 "Reinforcement Learning for Integer Programming: Learning to Cut" Yunhao Tang - Columbia University Abstract: Integer programming is a general optimization framework with a wide variety of applications. As Integer Programs (IPs) model man

From playlist Deep Learning and Combinatorial Optimization 2021

Nexus Trimester - Babak Hassibi (Caltech)

Simple Algorithms and Guarantees for Low Rank Matrix Completion over ... Babak Hassibi (Caltech) February 23, 2016 Abstract: Let [Math Processing Error] be a [Math Processing Error]-by-[Math Processing Error] matrix with entries in [Math Processing Error] and rank [Math Processing Error]

From playlist Nexus Trimester - 2016 - Fundamental Inequalities and Lower Bounds Theme

Linear Transformations

Showing something is a linear transformation Check out my Linear Equations playlist: https://www.youtube.com/playlist?list=PLJb1qAQIrmmD_u31hoZ1D335sSKMvVQ90 Subscribe to my channel: https://www.youtube.com/channel/UCoOjTxz-u5zU0W38zMkQIFw

From playlist Linear Transformations

Lec 18 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005

Lecture 18: Shortest Paths II: Bellman-Ford, Linear Programming, Difference Constraints View the complete course at: http://ocw.mit.edu/6-046JF05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503),