Search Results for author: Andreas Schmidt

Found 3 papers, 2 papers with code

Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring

1 code implementation11 Jul 2022 Al-Harith Farhad, Ioannis Sorokos, Andreas Schmidt, Mohammed Naveed Akram, Koorosh Aslansefat, Daniel Schneider

Limitations in setting SafeML up properly include the lack of a systematic approach for determining, for a given application, how many operational samples are needed to yield reliable distance information as well as to determine an appropriate distance threshold.

BIG-bench Machine Learning Traffic Sign Recognition

It's AI Match: A Two-Step Approach for Schema Matching Using Embeddings

no code implementations8 Mar 2022 Benjamin Hättasch, Michael Truong-Ngoc, Andreas Schmidt, Carsten Binnig

Since data is often stored in different sources, it needs to be integrated to gather a global view that is required in order to create value and derive knowledge from it.

Attribute Data Integration

DeepDB: Learn from Data, not from Queries!

1 code implementation2 Sep 2019 Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig

The typical approach for learned DBMS components is to capture the behavior by running a representative set of queries and use the observations to train a machine learning model.

Databases

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