Multiple-criteria decision analysis
In applied mathematics and decision making, the aggregated indices randomization method (AIRM) is a modification of a well-known aggregated indices method, targeting complex objects subjected to multi-criteria estimation under uncertainty. AIRM was first developed by the Russian naval applied mathematician Aleksey Krylov around 1908. The main advantage of AIRM over other variants of aggregated indices methods is its ability to cope with poor-quality input information. It can use non-numeric (ordinal), non-exact (interval) and non-complete expert information to solve multi-criteria decision analysis (MCDM) problems. An exact and transparent mathematical foundation can assure the precision and fidelity of AIRM results. (Wikipedia).
Determining Inverse Matrices Using Augmented Matrices
This video explains how to determine the inverse of a matrix using augmented matrices. http://mathispower4u.yolasite.com/ http://mathispower4u.wordpress.com/
From playlist Inverse Matrices
C# Wait Explained | C# Wait Example | C# Wait Task Tutorial | C# Tutorial For Beginners |Simplilearn
π₯Post Graduate Program In Full Stack Web Development: https://www.simplilearn.com/pgp-full-stack-web-development-certification-training-course?utm_campaign=CSharpWait-KezYq745G64&utm_medium=DescriptionFF&utm_source=youtube π₯Caltech Coding Bootcamp (US Only): https://www.simplilearn.com/cod
From playlist C# Training π₯[2022 Updated]
Random Forest Algorithm | Random Forest Complete Explanation | Data Science Training | Edureka
π₯Edureka Data Scientist Course Master Program https://www.edureka.co/masters-program/data-scientist-certification (Use Code "πππππππππ") This Edureka tutorial explains Random Forest Algorithm in detail, important terms in random forest, working of random forest classifier, along with exa
From playlist Data Science Training Videos
Composition of inverses using a triangle with variables
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Gilles Stoltz: Robust sequential learning with applications to the forecasting [...]
Abstract: Sometimes, you feel you're spoilt for choice: there are so many good predictors that you could use! Why select and focus on just one? I will review the framework of robust online aggregation (also known as prediction of individual sequences or online aggregation of expert advice)
From playlist Probability and Statistics
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Stanford Seminar - WeBuildAI: Participatory framework for algorithmic governance
Min Kyung Lee Carnegie Mellon University January 18, 2019 Algorithms increasingly govern societal functions, impacting multiple stakeholders and social groups. How can we design these algorithms to balance varying interests and promote social welfare? As one response to this question, I p
From playlist Stanford Seminars
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
Author Interview - Equivariant Subgraph Aggregation Networks
Paper link: https://arxiv.org/abs/2110.02910 Primary authors: Beatrice Bevilacqua (@beabevi_), Fabrizio Frasca (@ffabffrasca), Derek Lim (@dereklim_lzh) Join my FREE course Basics of Graph Neural Networks (https://www.graphneuralnets.com/p/basics-of-gnns/?src=yt)
From playlist Graph Neural Networks
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 Johnβs 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
Network Analysis. Lecture 18. Link prediction.
Link prediction problem. Proximity measures. Scoring algorithms. Prediction by supervised learning. Performance evaluation. Lecture slides: http://www.leonidzhukov.net/hse/2015/networks/lectures/lecture18.pdf
From playlist Structural Analysis and Visualization of Networks.
Epilogue - The map of machine learning. Brief views of Bayesian learning and aggregation methods. Lecture 18 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/machine-learnin
From playlist Machine Learning Course - CS 156
Using composition of inverses using triangles
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Find the value of the trigonometric expression using inverse
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Nucleation in protein folding by Jayant Udgaonkar
Conference and School on Nucleation Aggregation and Growth URL: https://www.icts.res.in/program/NAG2010 DATES: Monday 26 July, 2010 - Friday 06 Aug, 2010 VENUE : Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru DESCRIPTION: Venue: Jawaharlal Nehru Centre for Advance
From playlist Conference and School on Nucleation Aggregation and Growth