Ad Network Tomography
Data Skeptic3 Okt 2022

Ad Network Tomography

Data sharing in the ad tech space has largely been a black box system. While it is obvious the data is being collected, the data sharing process is obscure to users. On the show today, Maaz Bin Musa and Rishab, both researchers at the University of Iowa, speak about the importance of data transparency and their tool, ATOM for data transparency. Listen to find out how ATOM uncovers data-sharing relationships in the ad-tech space.

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Episoder(601)

Shapley Values

Shapley Values

Kyle and Linhda discuss how Shapley Values might be a good tool for determining what makes the cut for a home renovation.

6 Mar 202020min

Anchors as Explanations

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We welcome back Marco Tulio Ribeiro to discuss research he has done since our original discussion on LIME. In particular, we ask the question Are Red Roses Red? and discuss how Anchors provide high pr...

28 Feb 202037min

Mathematical Models of Ecological Systems

Mathematical Models of Ecological Systems

22 Feb 202036min

Adversarial Explanations

Adversarial Explanations

Walt Woods joins us to discuss his paper Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness with co-authors Jack Chen and Christof Teusche...

14 Feb 202036min

ObjectNet

ObjectNet

Andrei Barbu joins us to discuss ObjectNet - a new kind of vision dataset. In contrast to ImageNet, ObjectNet seeks to provide images that are more representative of the types of images an autonomous ...

7 Feb 202038min

Visualization and Interpretability

Visualization and Interpretability

Enrico Bertini joins us to discuss how data visualization can be used to help make machine learning more interpretable and explainable. Find out more about Enrico at http://enrico.bertini.io/. More fr...

31 Jan 202035min

Interpretable One Shot Learning

Interpretable One Shot Learning

We welcome Su Wang back to Data Skeptic to discuss the paper Distributional modeling on a diet: One-shot word learning from text only.

26 Jan 202030min

Fooling Computer Vision

Fooling Computer Vision

Wiebe van Ranst joins us to talk about a project in which specially designed printed images can fool a computer vision system, preventing it from identifying a person.  Their attack targets the popula...

22 Jan 202025min

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