The theta-criterion (also named θ-criterion) is a constraint on x-bar theory that was first proposed by Noam Chomsky as a rule within the system of principles of the government and binding theory, called theta-theory (θ-theory). As theta-theory is concerned with the distribution and assignment of theta-roles (a.k.a. thematic roles), the theta-criterion describes the specific match between arguments and theta-roles (θ-roles) in logical form (LF): Being a constraint on x-bar theory, the criterion aims to parse out ill-formed sentences. Thus, if the number or categories of arguments in a sentence does not meet the theta-role assigner's requirement in any given sentence, that sentence will be deemed ungrammatical. . In other words, theta-criterion sorts sentences into grammatical and ungrammatical bins based on c-selection and s-selection. (Wikipedia).
Calculus - Find the limit of a function using epsilon and delta
This video shows how to use epsilon and delta to prove that the limit of a function is a certain value. This particular video uses a linear function to highlight the process and make it easier to understand. Later videos take care of more complicated functions and using epsilon and delta
From playlist Calculus
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From playlist Quick Machine Learning Concepts
Epsilon-Delta Definition of a Limit (Not Examinable)
This video introduces the formal definition for the limit of a function at a point. Presented by Norman Wildberger of the School of Mathematics and Statistics, UNSW.
From playlist Mathematics 1A (Calculus)
Big-Theta Reflexive - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Big-Theta Practice - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Calculus - Find the limit of a function using epsilon and delta (2)
This video walks through another example of how to find an appropriate delta for proving a limit is a certain value. In this particular video we deal with the case that our interval around x is not symmetrical. For this instance we choose delta to be a minimum distance to the ends of the
From playlist Calculus
Neural Networks – An overview on Torch’s nn package Full project: https://github.com/Atcold/torch-Video-Tutorials Regression example: https://github.com/Atcold/torch-Machine-learning-with-Torch Notes: 54:36 – X[i] should be X[i + j] 54:44 – Y[i] should be Y[i + j] 54:56 – Y[i] should be
From playlist Deep-Learning-Course
Giovanni Forni: On the ergodicity of billiards in non-rational polygons
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Dynamical Systems and Ordinary Differential Equations
Jean-Marc Bardet: Consistent model selection criteria and goodness-of-fit test for common time...
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 02, 2020 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians
From playlist Virtual Conference
UCI Physics 3C: Basic Physics III (Fall 2013) Lec 18. Basic Physics III View the complete course: http://ocw.uci.edu/courses/physics_3c_basic_physics_iii.html Instructor: Michael Smy, Ph.D. License: Creative Commons CC-BY-SA Terms of Use: http://ocw.uci.edu/info More courses at http://ocw
From playlist Physics 3C: Basic Physics III
L16.2 LMS Estimation in the Absence of Observations
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
Daniele Agostini - Curves and theta functions: algebra, geometry & physics
Riemann’s theta function is a central object throughout mathematics, from algebraic geometry to number theory, and from mathematical physics to statistics and cryptography. One of my long term projects is to develop a program to study and connect the various aspects - geometric, computatio
From playlist Research Spotlight
Robert Tichy: Metric Discrepancy Theory
CIRM HYBRID EVENT Recorded during the meeting " Diophantine Problems, Determinism and Randomness" the February 04, 2021 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathem
From playlist Analysis and its Applications
Math 135 Complex Analysis Lecture 13 030515: Poisson Integral Formula; Sequences and Series
Poisson integral formula; quick (?) review of sequences and series: convergence, Cauchy sequence; series (sequence of partial sums), Cauchy criterion; proof of Divergence test; absolute convergence; absolute convergence implies convergence (via Cauchy Criterion); uniform convergence of a s
From playlist Course 8: Complex Analysis
Gilles Pagès: CVaR hedging using quantization based stochastic approximation algorithm
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Analysis and its Applications
This video covers Section 27.6 of Cutnell & Johnson Physics 10e, by David Young and Shane Stadler, published by John Wiley and Sons. The lecture is part of the course General Physics - Life Sciences I and II, taught by Dr. Boyd F. Edwards at Utah State University. This video was produced
From playlist Lecture 27. Interference and the Wave Nature of Light
Bayesian analysis with Linear Regression
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From playlist Quick Machine Learning Concepts