How a Computer know a Sentence is Grammatical: Context Free Grammars [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
7.1: Intro to Session 7: Context-Free Grammar - Programming with Text
This video introduces Session 7: Context-Free Grammar from the ITP course "Programming from A to Z". A Context-Free Grammar is a set of recursive "replacement" rules to generate text. In this session, I discuss two JavaScript libraries: Tracery and RiTa.js for working with context-free gr
From playlist Programming with Text - All Videos
An Overview of Predicate Logic for Linguists - Semantics in Linguistics
This video covers predicate logic in #semantics for #linguistics. We talk about predicates, quantifiers (for all, for some), how to translate sentences into predicate logic, scope, bound variables, free variables, and assignment functions. Join this channel to get access to perks: https:/
From playlist Semantics in Linguistics
Probabilistic logic programming and its applications - Luc De Raedt, Leuven
Probabilistic programs combine the power of programming languages with that of probabilistic graphical models. There has been a lot of progress in this paradigm over the past twenty years. This talk will introduce probabilistic logic programming languages, which are based on Sato's distrib
From playlist Logic and learning workshop
NOUN PHRASES - ENGLISH GRAMMAR
We discuss noun phrases. Noun phrases consist of a head noun, proper name, or pronoun. Noun phrases can be modified by adjective phrases or other noun phrases. Noun phrases take determiners as specifiers. We also draw trees for noun phrase. you want to support the channel, hit the "JOIN"
From playlist English Grammar
Fellow Short Talks: Dr Charles Sutton, Edinburgh University
Charles Sutton is a Reader (equivalent to Associate Professor: http://bit.ly/1W9UhqT) in Machine Learning at the University of Edinburgh. He has over 50 publications in a broad range of applications of probabilistic machine learning. His work in machine learning for software engineering ha
From playlist Short Talks
Building context-free grammars: Theory of Computation (Mar 12 2021)
Context free grammars! This is a recording of a live class for Math 3342, Theory of Computation, an undergraduate course for math & computer science majors at Fairfield University, Spring 2021. Class website: http://cstaecker.fairfield.edu/~cstaecker/courses/2021s3342/
From playlist Math 3342 (Theory of Computation) Spring 2021
How to Parse a Sentence with the CYK Algorithm [Lecture]
Dependency Parsing: https://youtu.be/ZT1Et5wd1SQ 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.) Mus
From playlist Computational Linguistics I
Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 18 – Constituency Parsing, TreeRNNs
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3wL2FCD Professor Christopher Manning, Stanford University http://onlinehub.stanford.edu/ Professor Christopher Manning Thomas M. Siebel Professor in Machine Lear
From playlist Stanford CS224N: Natural Language Processing with Deep Learning Course | Winter 2019
Paola Cantù : Logic and Interaction:pragmatics and argumentation theory
HYBRID EVENT Recorded during the meeting "Logic and transdisciplinarity" the February 11, 2022 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on CIRM's Audiov
From playlist Logic and Foundations
Matthijs Vákár: Mathematical foundations of automatic differentiation
HYBRID EVENT Recorded during the meeting "Logic of Probabilistic Programming" the January 31, 2022 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on CIRM's Aud
From playlist Virtual Conference
CMU Neural Nets for NLP 2017 (13): Parsing With Dynamic Programs
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