High-dimensional statistics

Computing z-scores(standard scores) and comparing them

Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Computing z-scores(standard scores) and comparing them

From playlist Statistics

Stanislav Nagy: Quantiles, depth, and symmetries: Geometry in multivariate statistics

There are tools of multivariate statistics with natural counterparts in geometry. We examine these connections and outline the amount of research that has been conducted in parallel in the two fields. Advances from geometry allow us to approach problems in multivariate statistics that were

From playlist Workshop: High dimensional measures: geometric and probabilistic aspects

PCA 2: Data manifolds in high-dimensional spaces

From playlist Dimensionality Reduction and PCA

Dimensional Analysis

We introduce the idea of dimensional analysis and its use in finding unknown quantities' dependence on relevant dimensionful variables.

From playlist Mathematical Physics I Uploads

Proportions, Ratios and Rates

This is an old video. See StatsMrR.com for access to hundreds of 1-3 minute, well-produced videos for learning Statistics. In this older video: Proportions are analyzed from a few perspectives, allowing us to more easily solve word problems and more easily set up proportions. Thinking o

From playlist Older Statistics Videos and Other Math Videos

Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

From playlist Statistics (Full Length Videos)

Joe Neeman: Gaussian isoperimetry and related topics I

The Gaussian isoperimetric inequality gives a sharp lower bound on the Gaussian surface area of any set in terms of its Gaussian measure. Its dimension-independent nature makes it a powerful tool for proving concentration inequalities in high dimensions. We will explore several consequence

From playlist Winter School on the Interplay between High-Dimensional Geometry and Probability

Mean, Median, and Mode

This video explains how to determine mean, median and mode. It also provided examples. http://mathispower4u.yolasite.com/

From playlist Statistics: Describing Data

Statistics - How to find outliers

This video covers how to find outliers in your data. Remember that an outlier is an extremely high, or extremely low value. We determine extreme by being 1.5 times the interquartile range above Q3 or below Q1. For more videos visit http://www.mysecretmathtutor.com

From playlist Statistics

Adel Javanmard

From playlist Plenary talks One World Symposium 2020

Fellow Short Talks: Professor Richard Samworth, Cambridge University

Bio Richard Samworth is Professor of Statistics in the Statistical Laboratory at the University of Cambridge and a Fellow of St John’s College. He received his PhD, also from the University of Cambridge, in 2004, and currently holds an EPSRC Early Career Fellowship. Research His main r

From playlist Short Talks

Bayesian data interpretation with large scale cosmological (...) - Jasche - Workshop 2 - CEB T3 2018

Jens Jasche (Stockholm University) / 25.10.2018 Bayesian data interpretation with large scale cosmological models ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/

From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology

Yanrong Yang - Can we trust PCA on non-stationary data?

Dr Yanrong Yang (ANU) presents “Can we trust PCA on non-stationary data?”, 13 August 2020. This seminar was organised by the Australian National University.

From playlist Statistics Across Campuses

Characterizing force-chain network architecture in granular materials - Danielle Bassett

Danielle Bassett University of Pennsylvania April 18, 2015 Force chains form heterogeneous physical structures that can constrain the mechanical stability and acoustic transmission of granular media. However, despite their relevance for predicting bulk properties of materials, there is no

From playlist Mathematics

Efficiently Learning Mixtures of Gaussians - Ankur Moitra

Efficiently Learning Mixtures of Gaussians Ankur Moitra Massachusetts Institute of Technology January 18, 2011 Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We provide a polynomial-time algorithm for this proble

From playlist Mathematics

Feature Ranking and Selection

Feature Ranking and Selection Teacher: Dr. Michael Pyrcz For more webinars & events please checkout: http://daytum.io/events Website: https://www.daytum.io/ Twitter: https://twitter.com/daytum_io?lang=en LinkedIn: https://www.linkedin.com/company/35593451 Data Science Education for Ener

From playlist daytum Free Webinar Series

A Theory of Neural Dimensionality, Dynamics and Measurement by Surya Ganguli

ICTS at Ten ORGANIZERS: Rajesh Gopakumar and Spenta R. Wadia DATE: 04 January 2018 to 06 January 2018 VENUE: International Centre for Theoretical Sciences, Bengaluru This is the tenth year of ICTS-TIFR since it came into existence on 2nd August 2007. ICTS has now grown to have more tha

From playlist ICTS at Ten

Statistical mechanics of deep learning by Surya Ganguli

Statistical Physics Methods in Machine Learning DATE: 26 December 2017 to 30 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the

From playlist Statistical Physics Methods in Machine Learning

Seminar 9: Surya Ganguli - Statistical Physics of Deep Learning

MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Surya Ganguli Describes how the application of methods from statistical physics to the analysis of high-dimensional data can provide theoretical insi

From playlist MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015

Dimensional Analysis Intro

An introduction to the idea of Dimensional Analysis

From playlist Mathematical Physics I Uploads