Contacts, Reach, Demographics for Approximation, sampling and compression in data science

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What is Approximation, sampling and compression in data science about?

Here is the podcast description for Approximation, sampling and compression in data science:

Programme Theme

Approximation theory is the study of simulating potentially extremely complicated functions, called target functions, with simpler, more easily computable functions called approximants. The purpose of the simulation could be to approximate values of the target function with respect to a given norm, to estimate the integral of the target function, or to compute its minimum value. Approximation theory's relationship with computer science and engineering encourages solutions that are efficient with regards to computation time and space. In addition, approximation theory problems may also deal with real-life restrictions on data, which can be incomplete, expensive, or noisy. As a result, approximation theory often overlaps with sampling and compression problems.

The main aim of this programme is to understand and solve challenging problems in the high-dimensional context, but this aim is dual. On one hand, we would like to use the high-dimensional context to understand classical approximation problems. For example, recent developments have revealed promising new directions towards a break-through in a set of classical unsolved problems related to sampling in hyperbolic cross approximations. On the other hand, we want to understand why classical multivariate approximation methods fail in the modern high-dimensional context and to find methods that will be better and more efficient for modern approximation in very high dimensions. This direction will focus on two conceptual steps: First, replacement of classical smoothness assumptions by structural assumptions, such as those of sparsity used by compressed sensing. Second, the use of a nonlinear method, for instance a greedy algorithm, to find an appropriate sparse approximant.

In order to achieve the goal the programme will bring together researchers from different fields to work in groups on modern problems of high-dimensional approximation and related topics. It will foster exchange between different groups of researchers and practitioners.

How many episodes of Approximation, sampling and compression in data science exist?

As of Aug 17th, 2025, Approximation, sampling and compression in data science has published 31 episodes.

When was the latest episode of Approximation, sampling and compression in data science?

The latest episode of Approximation, sampling and compression in data science was published on Jun 13th, 2019

When did Approximation, sampling and compression in data science launch?

Approximation, sampling and compression in data science launched its first episode on Feb 12th, 2019.

Is Approximation, sampling and compression in data science explicit?

The content of Approximation, sampling and compression in data science is not explicit.

Who is the author of Approximation, sampling and compression in data science?

Approximation, sampling and compression in data science is created by Arnel Hernandez.

Which podcast categories does Approximation, sampling and compression in data science belong to?

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Approximation, sampling and compression in data science

Arnel Hernandez
Approximation, sampling and compression in data science

Approximation, sampling and compression in data science

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How do I contact Approximation, sampling and compression in data science?

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What is Approximation, sampling and compression in data science about?

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Approximation, sampling and compression in data science

Arnel Hernandez Approximation, sampling and compression in data science

Approximation, sampling and compression in data science

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Frequently Asked Questions about Approximation, sampling and compression in data science

How do I contact Approximation, sampling and compression in data science?

How many listens/downloads does Approximation, sampling and compression in data science get?

Does Approximation, sampling and compression in data science accept guest interviews?

How much does it cost to advertise on Approximation, sampling and compression in data science?

Where does Approximation, sampling and compression in data science rank on Apple Podcasts charts?

Where does Approximation, sampling and compression in data science rank on Spotify's podcast charts?

Which brands have sponsored Approximation, sampling and compression in data science?

What is Approximation, sampling and compression in data science about?

How many episodes of Approximation, sampling and compression in data science exist?

When was the latest episode of Approximation, sampling and compression in data science?

When did Approximation, sampling and compression in data science launch?

Is Approximation, sampling and compression in data science explicit?

Who is the author of Approximation, sampling and compression in data science?

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Arnel Hernandez
Approximation, sampling and compression in data science

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