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L1 and L2 Norms and Regularization

Towards AI

Most, if not all data scientists are familiar with l1 and l2 regularization. However, what may not be as apparent, is why they’re called l1 and l2 regularization, and how exactly they work. In this…

Bayesian Priors and Regularization Penalties

Towards Data Science

Bayesian methods of performing machine learning offer several advantages over their counterparts, notably the ability to estimate uncertainty and the option to encode contextual knowledge as prior…

Why Norms Matters — Machine Learning

Towards Data Science

Evaluation is a crucial step in all modeling and machine learning problems. Since we are often making predictions on entire datasets, providing a single number that summarizes the performance of our…

torch.linalg.matrix_norm

PyTorch documentation

Computes a matrix norm. If A is complex valued, it computes the norm of A .abs() Support input of float, double, cfloat and cdouble dtypes. Also supports batches of matrices: the norm will be computed...

torch.linalg.norm

PyTorch documentation

Computes a vector or matrix norm. Supports input of float, double, cfloat and cdouble dtypes. Whether this function computes a vector or matrix norm is determined as follows: If dim is an int , the ve...

Scaling the regularization parameter for SVCs

Scikit-learn Examples

Scaling the regularization parameter for SVCs The following example illustrates the effect of scaling the regularization parameter when using Support Vector Machines for classification . For SVC class...

torch.nn.utils.clip_grad_norm_

PyTorch documentation

Clips gradient norm of an iterable of parameters. The norm is computed over all gradients together, as if they were concatenated into a single vector. Gradients are modified in-place. parameters ( Ite...

Vector Norms in Machine Learning

Towards Data Science

A guide to p-norms. Photo by Markus Winkler on Unsplash If you are reading this post, it is likely that you already know what vectors are and their indispensable place in Machine Learning. To recap, ...

Gentle Introduction to Vector Norms in Machine Learning

Machine Learning Mastery

Last Updated on October 17, 2021 Calculating the length or magnitude of vectors is often required either directly as a regularization method in machine learning, or as part of broader vector or matrix...

torch.nn.utils.parametrizations.spectral_norm

PyTorch documentation

Applies spectral normalization to a parameter in the given module. When applied on a vector, it simplifies to Spectral normalization stabilizes the training of discriminators (critics) in Generative A...

torch.linalg.vector_norm

PyTorch documentation

Computes a vector norm. If x is complex valued, it computes the norm of x .abs() Supports input of float, double, cfloat and cdouble dtypes. This function does not necessarily treat multidimensonal x ...