In ancient history, the concepts of chance and randomness were intertwined with that of fate. Many ancient peoples threw dice to determine fate, and this later evolved into games of chance. At the same time, most ancient cultures used various methods of divination to attempt to circumvent randomness and fate. Beyond religion and games of chance, randomness has been attested for sortition since at least ancient Athenian democracy in the form of a kleroterion. The formalization of odds and chance was perhaps earliest done by the Chinese 3,000 years ago. The Greek philosophers discussed randomness at length, but only in non-quantitative forms. It was only in the sixteenth century that Italian mathematicians began to formalize the odds associated with various games of chance. The invention of modern calculus had a positive impact on the formal study of randomness. In the 19th century the concept of entropy was introduced in physics. The early part of the twentieth century saw a rapid growth in the formal analysis of randomness, and mathematical foundations for probability were introduced, leading to its axiomatization in 1933. At the same time, the advent of quantum mechanics changed the scientific perspective on determinacy. In the mid to late 20th-century, ideas of algorithmic information theory introduced new dimensions to the field via the concept of algorithmic randomness. Although randomness had often been viewed as an obstacle and a nuisance for many centuries, in the twentieth century computer scientists began to realize that the deliberate introduction of randomness into computations can be an effective tool for designing better algorithms. In some cases, such randomized algorithms are able to outperform the best deterministic methods. (Wikipedia).
The Most Powerful Tool Based Entirely On Randomness
We see the effects of randomness all around us on a day to day basis. In this video we’ll be discussing a couple of different techniques that scientists use to understand randomness, as well as how we can harness its power. Basically, we'll study the mathematics of randomness. The branch
From playlist Classical Physics by Parth G
PMSP - Computational pseudo-randomness and extractors I - Russell Impagliazzo
Russell Impagliazzo UC San Diego and Institute for Advanced Study June 14, 2010 For more videos, visit http://video.ias.edu
From playlist Mathematics
Randomness Quiz - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
9mat Probability Quiz 3 Randomness Answers
9mat Probability Quiz 3 Randomness Answers
From playlist 2014 9mat
Prob & Stats - Random Variable & Prob Distribution (1 of 53) Random Variable
Visit http://ilectureonline.com for more math and science lectures! In this video I will define and gives an example of what is a random variable. Next video in series: http://youtu.be/aEB07VIIfKs
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
Avi Wigderson: Randomness and pseudorandomness
Abstract: The talk is aimed at a general audience, and no particular background will be assumed. Is the universe inherently deterministic or probabilistic? Perhaps more importantly - can we tell the difference between the two? Humanity has pondered the meaning and utility of randomness fo
From playlist Abel Lectures
Introduction to Random Variables
Introduction to random variables and probability distribution functions. More free lessons at: http://www.khanacademy.org/video?v=IYdiKeQ9xEI
From playlist Statistics
(PP 3.1) Random Variables - Definition and CDF
(0:00) Intuitive examples. (1:25) Definition of a random variable. (6:10) CDF of a random variable. (8:28) Distribution of a random variable. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5DB5E4
From playlist Probability Theory
Online List Labeling: Breaking the log2 n Barrier - Nicole Wein
Computer Science/Discrete Mathematics Seminar II Topic: Online List Labeling: Breaking the log2 n Barrier Speaker: Nicole Wein Affiliation: Rutgers University Date: December 06, 2022 The online list labeling problem is a basic primitive in data structures. The goal is to store a dynami
From playlist Mathematics
Lecture 15 - ARIMA & GARCH Models
This is Lecture 15 of the COMP510 (Computational Finance) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Hong Kong University of Science and Technology in 2008. The lecture slides are available at: http://www.algorithm.cs.sunysb.edu/computationalfinance/pd
From playlist COMP510 - Computational Finance - 2007 HKUST
Edward Witten: On the Shoulders of Giants
Acknowledging the scientists who blazed intellectual trails before him, Isaac Newton wrote, “If I have seen a little further it was by standing on the shoulders of giants.” In this special annual series, we invite our audience to stand on the shoulders of a modern-day giant. In 2015, we
From playlist Watch Our Most Popular Programs
[Rust Programming] Learning to make a Roguelike - Day 34
[Recorded on 19 November, 2021] I've been playing Roguelikes for many years, and I've always thought about making one! Combine that with a desire to learn Rust, and we've got a match made in heaven. This session was recorded live from twitch on 19 November. I'm using the Roguelike Tutori
From playlist [Rust Programming] Writing Roguelike using RLTK
Control, Confidentiality, and the Right to be Forgotten
A Google TechTalk, presented by Aloni Cohen, 2022/10/12 Differential Privacy for ML seminar series
From playlist Differential Privacy for ML
Random Processes and Stationarity
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduction to describing random processes using first and second moments (mean and autocorrelation/autocovariance). Definition of a stationa
From playlist Random Signal Characterization
Deep Reinforcement Learning of Marked Temporal Point Processes by Abir De
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)
“Data-Driven Pricing” – Prof. Omar Besbes
Pricing is central to many industries and academic disciplines ranging from Operations Research to Economics and Computer Science. At the heart of pricing lies a fundamental informational dimension regarding the level of knowledge about customers' values. In practice, the latter comes from
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
L22.8 The Fresh Start Property and Its Implications
MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
From playlist MIT RES.6-012 Introduction to Probability, Spring 2018
From playlist Courses and Series
Randomness - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Stream Archive: Logging out of Auth0 (2022-05-04)
I'm experimenting with Yew.rs and building a Brooks Builds website. But before I do I want to experiment a bit with Yew.rs. We've got login working. In this stream I get logout working as well. Yew Component Library Code: [https://github.com/brooks-builds/yew_component_librar
From playlist Yew.rs Playground