Dependent random choice - Jacob Fox
Marston Morse Lectures Topic: Dependent random choice Speaker: Jacob Fox, Stanford University Date: October 26, 2016 For more videos, visit http://video.ias.edu
From playlist Mathematics
(ML 11.4) Choosing a decision rule - Bayesian and frequentist
Choosing a decision rule, from Bayesian and frequentist perspectives. To make the problem well-defined from the frequentist perspective, some additional guiding principle is introduced such as unbiasedness, minimax, or invariance.
From playlist Machine Learning
How to Determine if Functions are Linearly Independent or Dependent using the Definition
How to Determine if Functions are Linearly Independent or Dependent using the Definition If you enjoyed this video please consider liking, sharing, and subscribing. You can also help support my channel by becoming a member https://www.youtube.com/channel/UCr7lmzIk63PZnBw3bezl-Mg/join Th
From playlist Zill DE 4.1 Preliminary Theory - Linear Equations
Find a 3rd Vector in R3 That Makes a Set of Vectors Dependent and Then Independent
This video explains how to find a third vector of a set of 2 vectors that will make the set dependent and then independent.
From playlist Linear Independence and Bases
Introduction to Linearly Independent and Linearly Dependent Sets of Vectors
This video introduced the topic of linearly independent and dependent sets of vectors.
From playlist Linear Independence and Bases
This video provides a lesson on dependent function and verifying given functions are linear dependent. Site: http://mathispower4u.com
From playlist Second Order Differential Equations
Prob & Stats - Random Variable & Prob Distribution (1 of 53) Random Variable
Visit http://ilectureonline.com for more math and science lectures! In this video I will define and gives an example of what is a random variable. Next video in series: http://youtu.be/aEB07VIIfKs
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
An Introduction to Linear Regression Analysis
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Lon
From playlist Linear Regression.
5. Forbidding a subgraph IV: dependent random choice
MIT 18.217 Graph Theory and Additive Combinatorics, Fall 2019 Instructor: Yufei Zhao View the complete course: https://ocw.mit.edu/18-217F19 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62qauV_CpT1zKaGG_Vj5igX Prof. Zhao discusses in this lecture the dependent random
From playlist MIT 18.217 Graph Theory and Additive Combinatorics, Fall 2019
Determine if the Functions are Linearly Independent or Linearly Dependent
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys How to determine if three functions are linearly independent or linearly dependent using the definition.
From playlist Differential Equations
Giovanni Peccati: Cancellations in random nodal sets
Abstract: I will discuss second order results for the length of nodal sets and the number of phase singularities associated with Gaussian random Laplace eigenfunctions, both on compact manifolds (the flat torus) and on subset of the plane. I will mainly focus on 'cancellation phenomena' fo
From playlist Probability and Statistics
CSDM - Choongbum Lee - September 28, 2015
http://www.math.ias.edu/calendar/event/83484/1443453300/1443456900
From playlist Computer Science/Discrete Mathematics
David Zywina, Computing Sato-Tate and monodromy groups.
VaNTAGe seminar on May 5, 2020. License: CC-BY-NC-SA Closed captions provided by Jun Bo Lau.
From playlist The Sato-Tate conjecture for abelian varieties
Universality in numerical computations with random data. Case studies - Percy Deift
Analysis Math-Physics Seminar Topic: Universality in numerical computations with random data. Case studies Speaker: Percy Deift Affiliation: New York University Date: Oct 13, 2016 For more videos, visit http://video.ias.edu
From playlist Mathematics
2020.05.28 Andrew Stuart - Supervised Learning between Function Spaces
Consider separable Banach spaces X and Y, and equip X with a probability measure m. Let F: X \to Y be an unknown operator. Given data pairs {x_j,F(x_j)} with {x_j} drawn i.i.d. from m, the goal of supervised learning is to approximate F. The proposed approach is motivated by the recent su
From playlist One World Probability Seminar
Modelling Passenger Behaviour on the Underground
About the event Using the London Underground as our primary example, we will discuss two main lines of work. In the first, we discuss a practical end-to-end model to infer changes in passenger behaviour based on unplanned disruption. This model takes into account user-level data to account
From playlist Data-Centric Engineering Seminar Series
Sandrine Péché: Eigenvalue distribution for non linear models of random matrices
The talk concerned with the asymptotic empirical eigenvalue distribution of a non linear random matrix ensemble. More precisely we consider $M= \frac{1}{m} YY^*$ with $Y=f(WX)$ where W and X are random rectangular matrices with i.i.d. centered entries. The function f is applied pointwise
From playlist Probability and Statistics
Probability Without Replacement (Dependent): Selecting Students in Order
This video explains how to determine the probability that two dependent events both occur. http//mathispower4u.com
From playlist Probability