In statistical decision theory, where we are faced with the problem of estimating a deterministic parameter (vector) from observations an estimator (estimation rule) is called minimax if its maximal risk is minimal among all estimators of . In a sense this means that is an estimator which performs best in the worst possible case allowed in the problem. (Wikipedia).
Minimax Approximation and the Exchange Algorithm
In this video we'll discuss minimax approximation. This is a method of approximating functions by minimisation of the infinity (uniform) norm. The exchange algorithm is an iterative method of finding the approximation which minimises the infinity norm. FAQ : How do you make these animatio
From playlist Approximation Theory
Confidence Intervals with Minitab Express - Means
This demonstration shows you how to construct confidence intervals for means with Minitab Express. This demonstration corresponds to the Introduction to Statistics, Think & Do textbook by Scott Stevens (http://www.StevensStats.com).
From playlist Minitab and Minitab Express Demonstrations
M17 Sample Size for Estimation
Find the sample size required to estimate population parameters using Minitab 17.
From playlist Minitab 17 Instructional Videos
Test for a Difference in Two Proportions, Minitab, Data in One Column
This demonstrates how to conduct a hypothesis test for a difference in two proportions. It uses Minitab when both samples are in one column. This demonstration corresponds to Introduction to Statistics, Think & Do, by Scott Stevens (http://www.StevensStats.com).
From playlist Minitab and Minitab Express Demonstrations
Test for a Difference in Means, Independent Samples, Minitab, Data in One Column
This demonstrates how to conduct a hypothesis test for a difference in means between independent samples. It uses Minitab with raw data and both samples are in one column. This demonstration corresponds to Introduction to Statistics, Think & Do, by Scott Stevens (http://www.StevensStats
From playlist Minitab and Minitab Express Demonstrations
Test for a Difference in Means, Independent Samples, Minitab, Data in Two Columns
This demonstrates how to conduct a hypothesis test for a difference in means between independent samples. It uses Minitab with raw data and each sample is in its own column. This demonstration corresponds to Introduction to Statistics, Think & Do, by Scott Stevens (www.StevensStats.com)
From playlist Minitab and Minitab Express Demonstrations
Confidence Intervals with Minitab Express: Means, z-distribution
This demonstration shows you how to construct a confidence interval about a population mean with Minitab Express under the unusual circumstance of knowing the population standard deviation. In practice this is seldom used and the more-popular t-test is used instead. This demonstration cor
From playlist Minitab and Minitab Express Demonstrations
Learning Minimax Estimators Via Online Learning by Praneeth Netrapalli
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Martin Wainwright: Privacy and statistical minimax: quantitative tradeoffs
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 Probability and Statistics
Fastest Identification in Linear Systems by Alexandre Proutiere
Program Advances in Applied Probability II (ONLINE) ORGANIZERS: Vivek S Borkar (IIT Bombay, India), Sandeep Juneja (TIFR Mumbai, India), Kavita Ramanan (Brown University, Rhode Island), Devavrat Shah (MIT, US) and Piyush Srivastava (TIFR Mumbai, India) DATE: 04 January 2021 to 08 Januar
From playlist Advances in Applied Probability II (Online)
Chao Gao: Statistical Optimality and Algorithms for Top-K Ranking - Lecture 2
CIRM VIRTUAL CONFERENCE In the first presentation, we will consider the top-K ranking problem. The statistical properties of two popular algorithms, MLE and rank centrality (spectral ranking) will be precisely characterized. In terms of both partial and exact recovery, the MLE achieves op
From playlist Virtual Conference
This demonstration shows you how to conduct an ANOVA test with Minitab. This demonstration corresponds to Introduction to Statistics, Think & Do, by Scott Stevens (http://www.StevensStats.com).
From playlist Minitab and Minitab Express Demonstrations
Isotonic regression in general dimensions – Richard Samworth, University of Cambridge
Many problems in science and engineering involve an underlying unknown complex process that depends on a large number of parameters. The goal in many applications is to reconstruct, or learn, the unknown process given some direct or indirect observations. Mathematically, such a problem can
From playlist Approximating high dimensional functions
Test for Mean Difference, Paired Data, Minitab, Raw Data in Two Columns
This demonstrates how to conduct a hypothesis test for a mean difference in paired data. It uses Minitab with raw data in two columns. This demonstration corresponds to Introduction to Statistics, Think & Do, by Scott Stevens (http://www.StevensStats.com).
From playlist Minitab and Minitab Express Demonstrations
Reinforcement Learning 10: Classic Games Case Study
David Silver, Research Scientist, discusses classic games as part of the Advanced Deep Learning & Reinforcement Learning Lectures.
From playlist DeepMind x UCL | Reinforcement Learning Course 2018
Coding Challenge 154: Tic Tac Toe AI with Minimax Algorithm
In this challenge I take the Tic Tac Toe game from coding challenge #149 and add an AI opponent for a human player by implenenting the Minimax algorithm. Code: https://thecodingtrain.com/challenges/154-tic-tac-toe-minimax 🕹️ p5.js Web Editor Sketch: https://editor.p5js.org/codingtrain/ske
From playlist Coding Challenges
Adaptive Estimation via Optimal Decision Trees by Subhajit Goswami
Program Advances in Applied Probability II (ONLINE) ORGANIZERS: Vivek S Borkar (IIT Bombay, India), Sandeep Juneja (TIFR Mumbai, India), Kavita Ramanan (Brown University, Rhode Island), Devavrat Shah (MIT, US) and Piyush Srivastava (TIFR Mumbai, India) DATE: 04 January 2021 to 08 Januar
From playlist Advances in Applied Probability II (Online)
Etienne Roquain: Sparse multiple testing: can one estimate the null distribution?
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 03, 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
Confidence Intervals with Minitab Express- Proportions
This demonstration shows you how to construct confidence intervals for a proportion with Minitab Express. This demonstration corresponds to the Introduction to Statistics, Think & Do textbook by Scott Stevens (http://www.StevensStats.com).
From playlist Minitab and Minitab Express Demonstrations
Nexus Trimester - Suresh Venkatasubramanian (University of Utah) 2/3
From Pigeons to Fano, and beyond Suresh Venkatasubramanian (University of Utah) February 17, 2016 Abstract: Fano's inequality can be viewed as capturing a deep interplay between information and computation. It links storage, reconstruction and transmission in one inequality, generalizing
From playlist Nexus Trimester - 2016 - Fundamental Inequalities and Lower Bounds Theme