Lecture 1 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, gives the introductory lecture for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that arise in engineering. Con
From playlist Lecture Collection | Convex Optimization
Akiyoshi Shioura: Analysis of L-convex Function Minimization Algorithms and App. to Auction Th.
We analyze minimization algorithms for L-convex functions in discrete convex analysis, and establish exact bounds for the number of iterations required by the steepest descent algorithm and its variants. We also mention the implication of our results to iterative auction algorithms in auct
From playlist HIM Lectures 2015
Lecture 7 | Convex Optimization I
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, expands upon his previous lectures on convex optimization problems for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization pro
From playlist Lecture Collection | Convex Optimization
Lecture 6 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his lecture on convex optimization problems for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that ar
From playlist Lecture Collection | Convex Optimization
Lecture 13 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his lecture on geometric problems for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that arise in eng
From playlist Lecture Collection | Convex Optimization
Geometric Algorithms: Graham & Jarvis - Lecture 10
All rights reserved for http://www.aduni.org/ Published under the Creative Commons Attribution-ShareAlike license http://creativecommons.org/licenses/by-sa/2.0/ Tutorials by Instructor: Shai Simonson. http://www.stonehill.edu/compsci/shai.htm Visit the forum at: http://www.coderisland.c
From playlist ArsDigita Algorithms by Shai Simonson
Lecture 26 - Heuristic Methods
This is Lecture 26 of the CSE373 (Analysis of Algorithms) taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 1997. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/1997/lecture21.pdf
From playlist CSE373 - Analysis of Algorithms - 1997 SBU
Graph Alg. IV: Intro to geometric algorithms - Lecture 9
All rights reserved for http://www.aduni.org/ Published under the Creative Commons Attribution-ShareAlike license http://creativecommons.org/licenses/by-sa/2.0/ Tutorials by Instructor: Shai Simonson. http://www.stonehill.edu/compsci/shai.htm Visit the forum at: http://www.coderisland.c
From playlist ArsDigita Algorithms by Shai Simonson
Coding Challenge #148: Gift Wrapping Algorithm (Convex Hull)
In this coding challenge, I implement the "Gift Wrapping algorithm" (aka Jarvis march) for calculating a convex hull in JavaScript. This is a foundational topic in computational geometry! 💻 Code: https://thecodingtrain.com/CodingChallenges/148-gift-wrapping Links discussed in this video:
From playlist Coding Challenges
Tropical Geometry - Lecture 9 - Tropical Convexity | Bernd Sturmfels
Twelve lectures on Tropical Geometry by Bernd Sturmfels (Max Planck Institute for Mathematics in the Sciences | Leipzig, Germany) We recommend supplementing these lectures by reading the book "Introduction to Tropical Geometry" (Maclagan, Sturmfels - 2015 - American Mathematical Society)
From playlist Twelve Lectures on Tropical Geometry by Bernd Sturmfels
Lecture 11 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, lectures on how statistical estimation can be used in convex optimization for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimizat
From playlist Lecture Collection | Convex Optimization
Cascadia Ruby 2014- The Science of Success
By, Davy Stevenson Software is approached mainly from the angle of engineering. Let's step back and take a look at software as science. How can we increase the quality of our code, tune our minds to efficiently solve problems, and correctly reapply known solutions to new problems? Learn a
From playlist Cascadia Ruby 2014
Deeparnab Chakrabarty: Provable Submodular Function Minimization via Fujishige Wolfe Algorithm
The Fujishige-Wolfe heuristic is empirically one of the fastest algorithms for Submodular Function Minimization and is based upon Wolfe's algorithm to find the nearest point on a polytope to the origin. There was no theoretical guarantees known for the same. In this work we give a converge
From playlist HIM Lectures 2015
Factorization through L2, Rounding and Duality Part 2 - Vijay Bhattiprolu
Computer Science/Discrete Mathematics Seminar II Topic: Factorization through L2, Rounding and Duality Part 2 Speaker: Vijay Bhattiprolu Affiliation: Member, School of Mathematics Date: November 24, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
Lecture 19 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, gives the final lecture on convex optimization for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that arise in
From playlist Lecture Collection | Convex Optimization
Ruby on Ales 2014 - Ruby as Science, Art & Craft
By Davy Stevenson Developers are encouraged, and sometimes required, to study Computer Science, however a large percentage of us are self-taught or have entered programming through related fields. This sits in stark contrast to most other engineering disciplines, and this diversity is pos
From playlist Ruby on Ales 2014
Lecture 14 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, gives a background lecture of numerical linear algebra for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that a
From playlist Lecture Collection | Convex Optimization