Regular semantics is a computing term which describes one type of guarantee provided by a data register shared by several processors in a parallel machine or in a network of computers working together. Regular semantics are defined for a variable with a single writer but multiple readers. These semantics are stronger than safe semantics but weaker than atomic semantics: they guarantee that there is a total order to the write operations which is consistent with real-time and that read operations return either the value of the last write completed before the read begins, or that of one of the writes which are concurrent with the read. (Wikipedia).
From playlist Computing for Data Analysis (Roger Peng)
Computational Semantics: How Computers Know what Words Mean [Lecture]
This is a single lecture from a course. If you you like the material and want more context (e.g., the lectures that came before), check out the whole course: https://boydgraber.org/teaching/CMSC_723/ (Including homeworks and reading.) Music: https://soundcloud.com/alvin-grissom-ii/review
From playlist Computational Linguistics I
Summary Simplifying rational expressions
Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational
From playlist Simplify Rational Expressions
Simplify a rational expression
Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational
From playlist Simplify Rational Expressions
REGEX Tutorial Regular Expressions
Best Regular Expressions Book : http://goo.gl/RFX7eJ Here I explain how Regular Expressions are used. I cover all of the codes and what they are used for. The goal is to teach you how to use regular expressions once and for all.
From playlist Regex Tutorial
Regular Expressions Introduction
This video provides a brief overview of regular expressions and basic Go examples.
From playlist Archive - Cloud Computing
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer/Fall 2016 PSY 523 Psychology and Language lectures covering material from Harley's The Psychology of Language: From Data to Theory. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdo
From playlist PSY 523 Psychology and Language
An Overview of Relations and Functions for Linguists - Semantics in Linguistics
In this video on #semantics in #linguistics we introduce relations and functions, talk about properties of relations and types of functions. Join this channel to get access to perks: https://www.youtube.com/channel/UCGYSfZbPp3BiAFs531PBY7g/join Instagram: http://instagram.com/TrevTutorOf
From playlist Semantics in Linguistics
Simplifying rational expression
Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational
From playlist Simplify Rational Expressions (Binomials) #Rational
RubyConf 2021 - Just-in-Time Compiling Ruby Regexps on TruffleRuby by Benoit Daloze and Josef Haider
TruffleRuby together with Truffle Regex can now execute Ruby Regexps up to 40 times faster than CRuby! This is possible by just-in-time compiling Ruby Regexps to machine code by using Truffle Regex, a Truffle language for regular expressions. Truffle Regex uses finite-state machines, a muc
From playlist RubyConf 2021
ACAI: Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
Toronto Deep Learning Series, 7-Feb-2019 For slides and more information, visit https://tdls.a-i.science/events/2019-02-07 UNDERSTANDING AND IMPROVING INTERPOLATION IN AUTOENCODERS VIA AN ADVERSARIAL REGULARIZER Autoencoders provide a powerful framework for learning compressed representa
From playlist Generative Models
Theory of Computation Recitation 3
Theory of Computation Recitation 3 aduni
From playlist [Shai Simonson]Theory of Computation
Data around us, like images and documents, are very high dimensional. Autoencoders can learn a simpler representation of it. This representation can be used in many ways: - fast data transfers across a network - Self driving cars (Semantic Segmentation) - Neural Inpainting: Completing sect
From playlist Algorithms and Concepts
27c3: Code deobfuscation by optimization (en)
Speaker: Branko Spasojevic Optimization algorithms present an effective way for removing most obfuscations that are used today. Much of the compiler theory can be applied in removing obfuscations and building fast and reliable deobfuscation systems. By understanding traditional optimizati
From playlist 27C3: We come in peace
Lecture 15/16 : Modeling hierarchical structure with neural nets
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 15A From Principal Components Analysis to Autoencoders 15B Deep Autoencoders 15C Deep autoencoders for document retrieval and visualization 15D Semantic hashing 15E Learning binary codes for image retrieval 15F Shallo
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]
CMU Neural Nets for NLP 2017 (14): Neural Semantic Parsing
This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers: * What is Graph-based Parsing? * Minimum Spanning Tree Parsing * Structured Training and Other Improvements * Dynamic Programming Methods for Phrase Structure Parsing * Reranking Slides: http:/
From playlist CMU Neural Nets for NLP 2017
Simplifying a rational expression by factoring
Learn how to simplify rational expressions. A rational expression is an expression in the form of a fraction where the numerator and/or the denominator are/is an algebraic expression. To simplify a rational expression, we factor completely the numerator and the denominator of the rational
From playlist Simplify Rational Expressions
VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained
❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany In this video I cover VQ-GAN or Taming Transformers for High-Resolution Image Synthesis. It uses modified VQ-VAEs and a powerful transformer (GPT-2) to synthesize high-res images. An important modification of V
From playlist Transformers