Tensor product via universality

Here we look at the universality-based definition of the tensor product

February 28, 2024 · 3 min · Pantelis Sopasakis

Making sense of tensors and tensor products

We are trying to make sense of tensors and the tensor product of vector spaces

February 16, 2024 · 17 min · Pantelis Sopasakis

Estimation Crash Course IV: Sufficient Statistics

Sufficient statistics

August 31, 2023 · 4 min · Pantelis Sopasakis

Estimation Crash Course III: Cramér-Rao bound

The Cramér-Rao Bound is a lower bound on the variance of an unbiased estimator. Here we focus on one-parameter models.

August 29, 2023 · 4 min · Pantelis Sopasakis

Estimation Crash Course II: Fisher information

Introduction of the notion of Fisher information: a quantity of central importance in statistics.

August 23, 2023 · 8 min · Pantelis Sopasakis

Estimation Crash Course I: Statistics and Estimators

Statistics and Estimators: definitions of statisics and an introduction to the concepts of bias and variance of an estimator; several examples.

August 20, 2023 · 6 min · Pantelis Sopasakis

Reading Vershynin's HDP II: Subgaussianity

We study the class of sub-Gaussian random variables: those random variables whose tails are dominated by a Gaussian. Such random variables satisfy Hoeffding-type bounds and possess several interesting properties. We also define the sub-Gaussian norm and study its properties.

June 29, 2023 · 13 min · Pantelis Sopasakis

Reading Vershynin's HDP I: Markov, Chernoff, Hoeffding

A result on the convergence of sample mean and notes on some standard concentration inequalities such as the Markov, Chernoff, Hoeffding, and Chernoff’s bounds

June 28, 2023 · 10 min · Pantelis Sopasakis

Projection on the epigraph of the squared Euclidean norm

How to project on the epigraph of the squared Euclidean norm

March 1, 2023 · 1 min · Pantelis Sopasakis

Beyond the Kalman Filter II: Moving horizon estimation

Moving horizon estimation

February 27, 2023 · 7 min · Pantelis Sopasakis