Chap16 SVD with applications part2
Lectures for the Flipped Classroom for Dr. Boult's course CS2300 Computational Linear Algebra using the book Linear Algebra: A Geometry Toolbox 3rd Edition ...
DrBoult
Gappy POD
WEBSITE: databookuw.com This lecture highlights the use of sparse sampling and POD modes to interpolate reconstructions of reduced order models.
Nathan Kutz
Chap16 SVD with applications part2
Lectures for the Flipped Classroom for Dr. Boult's course CS2300 Computational Linear Algebra using the book Linear Algebra: A Geometry Toolbox 3rd Edition ...
DrBoult
Least Squares for Data Science using Julia
Least Squares and Data Fitting with Julia. This includes an overview of Gradient Descent, the Normal Equations, the pseudo-inverse, QR factorization , SVD ...
One on Epsilon
11. Minimizing _x_ Subject to Ax = b
MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: ...
MIT OpenCourseWare
SVD: Optimal Truncation [Matlab]
This video describes how to optimally truncate the singular value decomposition (SVD) for noisy data (Matlab code). See paper by Gavish and Donoho "The ...
Steve Brunton
Multiple Input Multiple Output MIMO Channel Estimation – Least Squares Maximum Likelihood ML
Want to learn about PYTHON and 5G Technology? Check out our 5G Python Program below! https://www.iitk.ac.in/mwn/python5G/ Welcome to the IIT Kanpur ...
NOC16 Jan-Mar EC01
Calibrating (Fitting) the Dupire Local Volatility Model
Discusses and explains the various methodologies for calibrating or fitting the Dupire Local Volatility model using the market prices of call options. It starts by ...
quantpie
Koopman Theory + Embeddings
This highlights how to think and construct Koopman embeddings for nonlinear dynamical systems. By appropriate choice of an observable (or coordinate ...
Nathan Kutz
Self Driving Cars - 3.2.2 - Feature Matching, Outlier Rejection, Visual Odometry
PLAYLIST: https://tinyurl.com/Self-Driving-Cars-Playlist See playlist description for topic headings.
Bob Trenwith
undergraduate machine learning 18: Least squares and the multivariate Gaussian
Least squares and the multivariate Gaussian. The slides are available here: http://www.cs.ubc.ca/~nando/340-2012/lectures.php This course was taught in 2012 ...
Nando de Freitas
Constrained Optimization of Quadratic Forms - Linear Algebra - F11
Tom Roby
POD introduction 1
Introduction to proper orthogonal decomposition and basis selection.
Nathan Kutz
Lecture 9 | Introduction to Linear Dynamical Systems
Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on autonomous linear dynamical systems for the course, ...
Stanford
MATLAB Nonlinear Optimization with fmincon
This step-by-step tutorial demonstrates fmincon solver on a nonlinear optimization problem with one equality and one inequality constraint.
APMonitor.com
线性代数库 LAPACK 介绍 (Linear Algebra PACKage)
LAPACK，其名为Linear Algebra PACKage的缩写，是一以Fortran编程语言写的，用于数值计算的函式集。 LAPACK提供了丰富的工具函式，可用于诸如解多元线性 ...
编程之美
Lecture: Linear Programming and Genetic Algorithms
We consider a number of more advanced optimization algorithms that include the genetic algorithm and linear programming for constrained optimization.
AMATH 301
Information Retrieval WS 17/18, Lecture 10: Latent Semantic Indexing
This is the recording of Lecture 10 from the course "Information Retrieval", held on 9th January 2018 by Prof. Dr. Hannah Bast at the University of Freiburg, ...
AD Lectures
Lec 14 | MIT 18.085 Computational Science and Engineering I
Numerical linear algebra: SVD and applications A more recent version of this course is available at: http://ocw.mit.edu/18-085f08 License: Creative Commons ...
MIT OpenCourseWare
Dr Egor Kraev - Easy Bayesian regularization for fitting financial time series and curves
www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the ...
PyData
Mini-Course: Reconstruction methods for sparse-data X-ray tomography - Class 01
Mini-Course: Reconstruction methods for sparse-data X-ray tomography - Class 01 Mini-Course: Samuli Siltanen (University of Helsinki, Finland) Title: ...
Instituto de Matemática Pura e Aplicada
Inverse Problems Lecture 14/2017: regularization parameter choice 1/2
Samuli Siltanen teaching the course "Inverse Problems" at the University of Helsinki. The lecture was given on March 17, 2017.
UH Inversion
XIII Brazilian Workshop on Continuous Optimization - Plenary Talk - Yuan Jin Yun
Speaker: Yuan Jin Yun Videos Playlist: http://bit.ly/2msbG3z Event page: http://bit.ly/2kWKvNJ Honoring Dr. Alfredo Iusem in his 70th birthday The XIII Brazilian ...
Instituto de Matemática Pura e Aplicada
JuMP-dev 2019 | Joaquim Dias Garcia | ParameterJuMP.jl
Registration for this years Virtual JuliaCon is available now (for free): https://juliacon.org/2020/tickets/. ParameterJuMP.jl Presented by Joaquim Dias Garcia at ...
The Julia Programming Language
Advances in high accuracy matrix computations - Zlatko Drmac, May 29, 2019
A talk by Zlatko Drmac at the workshop Advances in Numerical Linear Algebra, May 29-30, 2019 held in the School of Mathematics at the University of ...
nla-group
Hogwild for Machine Learning on Multicore
This program provides both theoretical and experimental evidence demonstrating the achievement of linear speedups on multicore workstations on several ...
UW Video
Nonlinear dimensionality reduction for faster kernel methods in machine learning - Christopher Musco
Computer Science/Discrete Mathematics Seminar I Topic: Nonlinear dimensionality reduction for faster kernel methods in machine learning. Speaker: ...
Institute for Advanced Study
Aedin Culhane, Workshop 200: An introduction to matrix factorization & principal component analysis
200: An introduction to matrix factorization and principal component analysis in R Aedin Culhane (Dana-Farber Cancer Institute) 1:00 PM - 1:55 PM EDT on ...
Bioconductor
AWS Partner Webinar: Object2Vec on Amazon SageMaker
Learn more about Amazon SageMaker Object2Vec at – https://amzn.to/2MNbiIa In this webinar which covers the Object2Vec algorithm used by Amazon ...
Amazon Web Services
Spotlight Talk: Convolutional Dictionary Learning through Tensor Factorization
Furong Huang, UC Irvine Representation Learning https://simons.berkeley.edu/talks/furong-huang-2017-03-29.
Simons Institute
Chebfun
Chebfun is a Matlab-based open-source software project for "numerical computing with functions" based on algorithms related to Chebyshev polynomials.
Society for Industrial and Applied Mathematics
Regression and Ax = b: Over- and under-determined systems
This lecture provides a framework for understanding simple regression architectures for over- and under-determined systems. The lecture is from Chapter 4.3 of ...
Nathan Kutz
Lecture 2 - Advanced AI | SVD, PseudoInverses, Linear Regression, L1, L2 Regularization
Learn with Daniel and Johnny about the complex web of AI topics including Singular Value Decomposition, PseudoInverses, Linear Regression, L1, L2 ...
UNSW Data Science Society
Covariance and correlation
This video explains what is meant by the covariance and correlation between two random variables, providing some intuition for their respective mathematical ...
Ben Lambert
ML-4-Linear Models (Lecture Part 1)
1. Begin: 0:00 2. Multi-variate Regression/Classification: 13:03 3. Linear Regression: 16:37 4. System of Linear Equations: 20:21 5. Cases for various systems: ...
SHALA 2020
Lecture30 (Data2Decision) Total Regression, part 1
Total regression, errors-in-variables regression, measurement error modeling, and the effective variance approximation. Course Website: ...
Chris Mack
POD carlberg 1
Current methods for nonlinear model reduction: from Galerkin projection to Petrov-Galerkin projection with applications in engineering and science.
Nathan Kutz
Genomics, Big Data, and Medicine Seminar Series – Kenneth Lange
"Next Generation Statistical Genetics” Dr. Kenneth Lange's research interests include human genetics, population modeling, biomedical imaging, computational ...
Mount Sinai Genetics and Genomic Sciences
Functional Data Analysis Under Shape Constraints - Srivastava - Workshop 2 - CEB T1 2019
Anuj Srivastava (Florida state Univ.) / 13.03.2019 Functional Data Analysis Under Shape Constraints. (Joint work with Sutanoy Dasgupta, Ian Jermyn, and ...
Institut Henri Poincaré
Tutorial 3.2: Lorenzo Rosasco - Machine Learning Part 2
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Lorenzo ...
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Quantum Algorithms for Classification
Iordanis Kerenidis, Université Paris Diderot https://simons.berkeley.edu/talks/iordanis-kerenidis-06-14-18 Challenges in Quantum Computation.
Simons Institute
Lecture - 41 Singular Value Decomposition
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nptelhrd
