Pseudorandom generators for polynomials

Pseudorandom Generators for Regular Branching Programs - Amir Yehudayoff

Amir Yehudayoff Institute for Advanced Study March 16, 2010 We shall discuss new pseudorandom generators for regular read-once branching programs of small width. A branching program is regular if the in-degree of every vertex in it is (either 0 or) 2. For every width d and length n, the p

From playlist Mathematics

Pseudorandom Generators for CCO[p]CCO[p] and the Fourier Spectrum... - Shachar Lovett

Shachar Lovett Institute for Advanced Study October 5, 2010 We give a pseudorandom generator, with seed length O(logn)O(logn), for CC0[p]CC0[p], the class of constant-depth circuits with unbounded fan-in MODpMODp gates, for prime pp. More accurately, the seed length of our generator is O(

From playlist Mathematics

Pseudorandom Generators for Read-Once ACC^0 - Srikanth Srinivasan

Srikanth Srinivasan DIMACS April 24, 2012 We consider the problem of constructing pseudorandom generators for read-once circuits. We give an explicit construction of a pseudorandom generator for the class of read-once constant depth circuits with unbounded fan-in AND, OR, NOT and generaliz

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Pseudorandom Number Generation and Stream Ciphers

Fundamental concepts of Pseudorandom Number Generation are discussed. Pseudorandom Number Generation using a Block Cipher is explained. Stream Cipher & RC4 are presented.

From playlist Network Security

Better Pseudorandom Generators from Milder Pseudorandom Restrictions - Parikshit Gopalan

Parikshit Gopalan Microsoft Research Silicon Valley, Mountain View, CA April 3, 2012 We present an iterative approach to constructing pseudorandom generators, based on the repeated application of mild pseudorandom restrictions. We use this template to construct pseudorandom generators for

From playlist Mathematics

What is the definition of a monomial and polynomials with examples

👉 Learn how to classify polynomials based on the number of terms as well as the leading coefficient and the degree. When we are classifying polynomials by the number of terms we will focus on monomials, binomials, and trinomials, whereas classifying polynomials by the degree will focus on

From playlist Classify Polynomials

Jonathan Katz - Introduction to Cryptography Part 1 of 3 - IPAM at UCLA

Recorded 25 July 2022. Jonathan Katz of the University of Maryland presents "Introduction to Cryptography I" at IPAM's Graduate Summer School Post-quantum and Quantum Cryptography. Abstract: This lecture will serve as a "crash course" in modern cryptography for those with no prior exposure

From playlist 2022 Graduate Summer School on Post-quantum and Quantum Cryptography

What is the definition of a polynomial with examples and non examples

👉 Learn how to classify polynomials based on the number of terms as well as the leading coefficient and the degree. When we are classifying polynomials by the number of terms we will focus on monomials, binomials, and trinomials, whereas classifying polynomials by the degree will focus on

From playlist Classify Polynomials

Patrick Morris - Triangle factors in pseudorandom graphs (CMSA Combinatorics Seminar)

Patrick Morris presents "Triangle factors in pseudorandom graphs," 31st March 2021 (CMSA Combinatorics Seminar) http://combinatorics-australasia.org/seminars.html

From playlist CMSA Combinatorics Seminar

24. Probabilistic Computation (cont.)

MIT 18.404J Theory of Computation, Fall 2020 Instructor: Michael Sipser View the complete course: https://ocw.mit.edu/18-404JF20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP60_JNv2MmK3wkOt9syvfQWY Quickly reviewed last lecture. Simulated read-once branching programs

From playlist MIT 18.404J Theory of Computation, Fall 2020

Multi-group fairness, loss minimization and indistinguishability - Parikshit Gopalan

Computer Science/Discrete Mathematics Seminar II Topic: Multi-group fairness, loss minimization and indistinguishability Speaker: Parikshit Gopalan Affiliation: VMware Research Date: April 12, 2022 Training a predictor to minimize a loss function fixed in advance is the dominant paradigm

From playlist Mathematics

Interview Igor Shparlinski : Jean Morlet Chair (First Semester 2014)

Jean-Morlet Chair on 'Number Theory and its Applications to Cryptography' Beneficiaries : Jean-Morlet Chair : Igor SHPARLINSKI School of Mathematics and Statistics University of New South Wales Sydney, Australia igor.shparlinski@unsw.edu.au Local project leader : David KOHEL I2M - Insti

From playlist Jean-Morlet Chair's holders - Interviews

Pseudorandomness from Shrinkage - Raghu Meka

Raghu Meka Institute for Advanced Study May 8, 2012 One powerful theme in complexity theory and pseudorandomness in the past few decades has been the use of lower bounds to give pseudorandom generators (PRGs). However, the general results using this hardness vs. randomness paradigm suffer

From playlist Mathematics

How do we multiply polynomials

👉 Learn how to multiply polynomials. To multiply polynomials, we use the distributive property. The distributive property is essential for multiplying polynomials. The distributive property is the use of each term of one of the polynomials to multiply all the terms of the other polynomial.

From playlist How to Multiply Polynomials

Indistinguishability Obfuscation from Well-Founded Assumptions - Huijia (Rachel) Lin

Computer Science/Discrete Mathematics Seminar I Topic: Indistinguishability Obfuscation from Well-Founded Assumptions Speaker: Huijia (Rachel) Lin Affiliation: University of Washington Date: November 16, 2020 For more video please visit http://video.ias.edu

From playlist Mathematics

Solving Laplacian Systems of Directed Graphs - John Peebles

Computer Science/Discrete Mathematics Seminar II Topic: Solving Laplacian Systems of Directed Graphs Speaker: John Peebles Affiliation: Member, School of Mathematics Date: March 02, 2021 For more video please visit http://video.ias.edu

From playlist Mathematics

Naming Polynomials 3

defining polynomials

From playlist Exponents

Giray Ökten: Number sequences for simulation - lecture 1

After an overview of some approaches to define random sequences, we will discuss pseudorandom sequences and low-discrepancy sequences. Applications to numerical integration, Koksma-Hlawka inequality, and Niederreiter’s uniform point sets will be discussed. We will then present randomized q

From playlist Probability and Statistics

How to factor complex polynomials

Free ebook http://bookboon.com/en/introduction-to-complex-numbers-ebook Every polynomial p(z) of degree n has at least one root in the set of complex numbers. That is, there is at least one number α such that p( α)=0. That is what we mean when we say that α is a root of a polynomial, p(

From playlist Intro to Complex Numbers