Time Complexity Analysis | What Is Time Complexity? | Data Structures And Algorithms | Simplilearn
This video covers what is time complexity analysis in data structures and algorithms. This Time Complexity tutorial aims to help beginners to get a better understanding of time complexity analysis. Following topics covered in this video: 00:00 What is Time Complexity Analysis 04:21 How t
From playlist Data Structures & Algorithms
Algorithms Explained: Computational Complexity
An overview of computational complexity including the basics of big O notation and common time complexities with examples of each. Understanding computational complexity is vital to understanding algorithms and why certain constructions or implementations are better than others. Even if y
From playlist Algorithms Explained
Big O Notation: A Few Examples
This video is about Big O Notation: A Few Examples Time complexity is commonly estimated by counting the number of elementary operations (elementary operation = an operation that takes a fixed amount of time to preform) performed in the algorithm. Time complexity is classified by the nat
From playlist Computer Science and Software Engineering Theory with Briana
Determine Time Complexity Function and Time Complexity Using Big-O Notation: f(n)=(cn(n-1))/2
This video explains how to determine the time complexity of given code. http://mathispower4u.com
From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)
This video provides a basic introduction to volume.
From playlist Volume and Surface Area (Geometry)
Lower Bound on Complexity - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Determine a Time Complexity of Code Using Big-O Notation: O(1), O(n), O(n^2)
This video explains how to determine the time complexity of given code. http://mathispower4u.com
From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)
Compare Algorithm Complexity Given The Execution Time as a Function
This video explains how to use a limit at infinity to compare the complexity (growth rate) of two functions. http://mathispower4u.com
From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)
Lecture 3 | Quantum Entanglements, Part 1 (Stanford)
Lecture 3 of Leonard Susskind's course concentrating on Quantum Entanglements (Part 1, Fall 2006). Recorded October 9, 2006 at Stanford University. This Stanford Continuing Studies course is the first of a three-quarter sequence of classes exploring the "quantum entanglements" in modern
From playlist Course | Quantum Entanglements: Part 1 (Fall 2006)
Designing explicit regularizers for deep models? - Tengyu Ma
Workshop on Theory of Deep Learning: Where next? Topic: Designing explicit regularizers for deep models? Speaker: Tengyu Ma Date: October 17, 2019 For more video please visit http://video.ias.edu
From playlist Workshop on Theory of Deep Learning: Where next?
Henry Adams (3/12/21): Vietoris-Rips thickenings: Problems for birds and frogs
An artificial distinction is to describe some mathematicians as birds, who from their high vantage point connect disparate areas of mathematics through broad theories, and other mathematicians as frogs, who dig deep into particular problems to solve them one at a time. Neither type of math
From playlist Vietoris-Rips Seminar
Serge Cantat - Random foldings of pentagons
Start with a pentagon in the euclidean plane, and consider the space of all pentagons with the same side lengths up to euclidean motion. This space is the real part of some K3 surface. Folding the pentagons along their diagonals, one obtains involutive automorphism of this K3 surface. I wi
From playlist Geometry in non-positive curvature and Kähler groups
Automorphisms of K3 surfaces – Serge Cantat – ICM2018
Dynamical Systems and Ordinary Differential Equations | Algebraic and Complex Geometry Invited Lecture 9.13 | 4.12 Automorphisms of K3 surfaces Serge Cantat Abstract: Holomorphic diffeomorphisms of K3 surfaces have nice dynamical properties. I will survey the main theorems concerning the
From playlist Algebraic & Complex Geometry
Lecture 3 | The Theoretical Minimum
January 23, 2012 - In this course, world renowned physicist, Leonard Susskind, dives into the fundamentals of classical mechanics and quantum physics. He discovers the link between the two branches of physics and ultimately shows how quantum mechanics grew out of the classical structure. I
From playlist Lecture Collection | The Theoretical Minimum: Quantum Mechanics
Complex dynamics and arithmetic equidistribution – Laura DeMarco – ICM2018
Dynamical Systems and Ordinary Differential Equations Invited Lecture 9.5 Complex dynamics and arithmetic equidistribution Laura DeMarco Abstract: I will explain a notion of arithmetic equidistribution that has found application in the study of complex dynamical systems. It was first int
From playlist Dynamical Systems and ODE
Lecture 12: Lebesgue Integrable Functions, the Lebesgue Integral and the Dominated Convergence...
MIT 18.102 Introduction to Functional Analysis, Spring 2021 Instructor: Dr. Casey Rodriguez View the complete course: https://ocw.mit.edu/courses/18-102-introduction-to-functional-analysis-spring-2021/ YouTube Playlist: https://www.youtube.com/watch?v=W2pw1JWc9k4&list=PLUl4u3cNGP63micsJp_
From playlist MIT 18.102 Introduction to Functional Analysis, Spring 2021
Lecture 2 | Quantum Entanglements, Part 1 (Stanford)
Lecture 2 of Leonard Susskind's course concentrating on Quantum Entanglements (Part 1, Fall 2006). Recorded October 2, 2006 at Stanford University. This Stanford Continuing Studies course is the first of a three-quarter sequence of classes exploring the "quantum entanglements" in modern
From playlist Course | Quantum Entanglements: Part 1 (Fall 2006)
Sensitivity Versus Block Sensitivity I - Hao Huang
Hao Huang University of California, Los Angeles; Member, School of Mathematics March 12, 2013 There are two important measures of the complexity of a boolean function: the sensitivity and block sensitivity. Whether or not they are polynomial related remains a major open question. In this t
From playlist Mathematics