Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Newton's method: Hessian and optimization
Graph Chatbot
Related lectures (44)
Linear Regression: Regularization
Log in to Mediaspace to watch this video
Covers linear regression, regularization, and probabilistic models in generating labels.
Logistic Regression: Classification
Log in to Mediaspace to watch this video
Covers supervised learning, classification using logistic regression, and challenges in optimization.
Method of Least Squares: Normal Equations
Log in to Mediaspace to watch this video
Explains the method of least squares and normal equations for finding optimal solutions.
Lagrangian Duality: Convex Optimization
Log in to Mediaspace to watch this video
Explores Lagrangian duality in convex optimization, transforming problems into min-max formulations and discussing the significance of dual solutions.
Diagonalization of Symmetric Matrices
Log in to Mediaspace to watch this video
Covers the diagonalization of symmetric matrices, the spectral theorem, and the use of spectral decomposition.
Orthogonal Projection: Euclidean Space
Log in to Mediaspace to watch this video
Explores orthogonal projection in Euclidean space, emphasizing uniqueness and calculation methods.
Linear Regression: Basics and Estimation
Log in to Mediaspace to watch this video
Covers the basics of linear regression and how to solve estimation problems using least squares and matrix notation.
Basics of linear regression model
Log in to Mediaspace to watch this video
Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.
Semi-Definite Programming
Log in to Mediaspace to watch this video
Covers semi-definite programming and optimization over positive semidefinite cones.
Least-Squares Approximation
Log in to Mediaspace to watch this video
Covers polynomial interpolation and least-squares approximations to minimize errors.
Orthogonality and Least Squares Method
Log in to Mediaspace to watch this video
Introduces orthogonal vectors, scalar product, Euclidean norm, Pythagorean theorem, and unit vectors.
Orthogonality and Least Squares Methods
Log in to Mediaspace to watch this video
Explores orthogonality, norms, and distances in vector spaces for solving linear systems.
Advanced Machine Learning: Ridge Regression
Log in to Mediaspace to watch this video
Covers linear regression basics, closed-form solutions, singularity, and regularizing techniques.
Multi-linear regression
Log in to Mediaspace to watch this video
Covers the concept of multi-linear regression and the least squares method for model fitting.
Applied Biostatistics: Bivariate Data Analysis
Log in to Mediaspace to watch this video
Explores bivariate data analysis in applied biostatistics, covering correlation, regression, model selection, and diagnostics.
Elements of Statistics: Probability, Distributions, and Estimation
Log in to Mediaspace to watch this video
Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.
QR Factorization and Least Squares
Log in to Mediaspace to watch this video
Explores QR factorization and the least squares method for solving systems of equations.
Untitled
Log in to Mediaspace to watch this video
Optimization algorithms
Log in to Mediaspace to watch this video
Covers optimization algorithms, focusing on Proximal Gradient Descent and its variations.
Single Inequality or Equality Constraint
Log in to Mediaspace to watch this video
Covers single inequality or equality constraints and necessary optimality conditions in optimization problems.
Previous
Page 2 of 3
Next