In cryptography, a distributed point function is a cryptographic primitive that allows two distributed processes to share a piece of information, and compute functions of their shared information, without revealing the information itself to either process. It is a form of secret sharing. Given any two values and one can define a point function (a variant of the Kronecker delta function) by That is, it is zero everywhere except at , where its value is . A distributed point function consists of a family of functions , parameterized by keys , and a method for deriving two keys and from any two input values and , such that for all , where denotes the bitwise exclusive or of the two function values. However, given only one of these two keys, the values of for that key should be indistinguishable from random. It is known how to construct an efficient distributed point function from another cryptographic primitive, a one-way function. In the other direction, if a distributed point function is known, then it is possible to perform private information retrieval.As a simplified example of this, it is possible to test whether a key belongs to replicated distributed database without revealing to the database servers (unless they collude with each other) which key was sought. To find the key in the database, create a distributed point function for and send the resulting two keys and to two different servers holding copies of the database. Each copy applies its function or to all the keys in its copy of the database, and returns the exclusive or of the results. The two returned values will differ if belongs to the database, and will be equal otherwise. (Wikipedia).
Cumulative Distribution Functions and Probability Density Functions
This statistics video tutorial provides a basic introduction into cumulative distribution functions and probability density functions. The probability density function or pdf is f(x) which describes the shape of the distribution. It can tell you if you have a uniform, exponential, or nor
From playlist Statistics
Represent a Discrete Function Using Ordered Pairs, a Table, and Function Notation
This video explains how to represent a discrete function given as points as ordered pairs, a table, and using function notation. http://mathispower4u.com
From playlist Introduction to Functions: Function Basics
Probability Distribution Functions and Cumulative Distribution Functions
In this video we discuss the concept of probability distributions. These commonly take one of two forms, either the probability distribution function, f(x), or the cumulative distribution function, F(x). We examine both discrete and continuous versions of both functions and illustrate th
From playlist Probability
Find the value of c so that the function is a density function and find the distribution function
Find the value of c so that the function is a density function and find the distribution function If you enjoyed this video please consider liking, sharing, and subscribing. Udemy Courses Via My Website: https://mathsorcerer.com My FaceBook Page: https://www.facebook.com/themathsorcerer
From playlist The Probability Distribution for a Continuous Random Variable
Overview of position functions in calculus and how they relate to velocity and acceleration.
From playlist Calculus
What are bounded functions and how do you determine the boundness
👉 Learn about the characteristics of a function. Given a function, we can determine the characteristics of the function's graph. We can determine the end behavior of the graph of the function (rises or falls left and rises or falls right). We can determine the number of zeros of the functi
From playlist Characteristics of Functions
How to determine if a set of points is a function, onto, one to one, domain, range
👉 Learn how to determine whether relations such as equations, graphs, ordered pairs, mapping and tables represent a function. A function is defined as a rule which assigns an input to a unique output. Hence, one major requirement of a function is that the function yields one and only one r
From playlist What is the Domain and Range of the Function
This video shows an example of how to determine the point of equilibrium given the supply and demand functions. Complete Video Library at www.mathispower4u.com
From playlist Business Applications of Integration
Math 131 092816 Continuity; Continuity and Compactness
Review definition of limit. Definition of continuity at a point; remark about isolated points; connection with limits. Composition of continuous functions. Alternate characterization of continuous functions (topological definition). Continuity and compactness: continuous image of a com
From playlist Course 7: (Rudin's) Principles of Mathematical Analysis
In this video we discuss the Gaussian (AKA Normal) probability distribution function. We show how it relates to the error function (erf) and discuss how to use this distribution analytically and numerically (for example when analyzing real-life sensor data or performing simulation of stoc
From playlist Probability
All of Statistics - Chapter 2 - Random Variables
🎬 This is my video summary of Chapter 2 (Random Variables) of "All of Statistics" by Larry Wasserman. 👉 If you are enjoying my work please subscribe to my youtube channel and consider supporting my work here: https://buymeacoffee.com/c3founder Read more about the "All of Statistics" vid
From playlist Summer of Math Exposition Youtube Videos
From playlist COMP0168 (2020/21)
Network Analysis. Lecture 2. Power laws.
Power law distribution. Scale-free networks.Pareto distribution, normalization, moments. Zipf law. Rank-frequency plot. Lecture slides: http://www.leonidzhukov.net/hse/2015/networks/lectures/lecture2.pdf
From playlist Structural Analysis and Visualization of Networks.
Generate uniform random distribution within a circle using Python 📚 🤔 🔢
In this micro tutorial, we explain how to generate uniformly distributed random numbers within a circle with radius R using Python. First, the algorithm and reopenings are given followed by simple Python implementation. The Python implementation using the random module to generate uniform
From playlist Engineering Animations
Анализ Социальных Сетей. Лекция 2.Степенные законы распределения
Слайды: http://www.leonidzhukov.net/hse/2014/socialnetworks/lectures/lecture2.pdf Степенное распределение. Масштабно-инвариантные сети (scale-free networks). Распределение Парето, нормализация, моменты. Закон Ципфа.Граф ранк-частота. Power laws. Power law distribution. Scale-free networ
From playlist Анализ Социальных Сетей. Курс НИУ ВШЭ
Slides and more information: https://mml-book.github.io/slopes-expectations.html
From playlist There and Back Again: A Tale of Slopes and Expectations (NeurIPS-2020 Tutorial)
From playlist COMP0168 (2020/21)
Uniform p-adic wave front sets and zero loci of function ...- R.Cluckers - Workshop 2 - CEB T1 2018
Raf Cluckers (CNRS – Université de Lille & KU Leuven) / 08.03.2018 Uniform p-adic wave front sets and zero loci of functions of C exp-class. I will recall some concrete parts of the course on motivic integration given at the IHP by Halupczok, and use it to define distributions of Cexp cl
From playlist 2018 - T1 - Model Theory, Combinatorics and Valued fields
Probability Density Function With Example | Probability And Statistics Tutorial | Simplilearn
🔥 Advanced Certificate Program In Data Science: https://www.simplilearn.com/pgp-data-science-certification-bootcamp-program?utm_campaign=ProbabilityDensityFunction-4FP6B5SrqKw&utm_medium=Descriptionff&utm_source=youtube 🔥 Data Science Bootcamp (US Only): https://www.simplilearn.com/data-sc
Introduction to Discrete and Continuous Functions
This video defines and provides examples of discrete and continuous functions.
From playlist Introduction to Functions: Function Basics