Lasso (statistics)

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Related lectures (30)

Page 3 of 3

Penalization in Ridge Regression

Covers penalization in ridge regression, emphasizing the trade-off between bias and variance in regression models.

Exponential of a Matrix

Explores the exponential of a matrix, properties, Frobenius norm, nilpotent matrices, commutativity, and system solutions.

Statistical Thermodynamics: Partition Functions and Quantum Statistics

Introduces partition functions, quantum statistics, and the Einstein model for molecular behavior.

Gradient Descent and Linear Regression

Covers stochastic gradient descent, linear regression, regularization, supervised learning, and the iterative nature of gradient descent.

Untitled

Polynomial Regression and Gradient Descent

Covers polynomial regression, gradient descent, overfitting, underfitting, regularization, and feature scaling in optimization algorithms.

Statistical Thermodynamics: Partition Function and Stirling Approximation

Explores the partition function and Stirling approximation in statistical thermodynamics, emphasizing the importance of recognizing higher order terms.

Regression Methods: Model Building and Inference

Covers analysis of variance, model building, variable selection, and function estimation in regression methods.

Statistical Thermodynamics: Maxwell-Boltzmann Distribution

Covers the Maxwell-Boltzmann distribution and entropy in composite systems.

Applications of GAMP

Delves into applying the GAMP algorithm to simplify the lasso problem and analyze optimization challenges in neural networks.