Aus SDQ-Institutsseminar
Termin (Alle Termine)
Datum Freitag, 12. Mai 2023
Uhrzeit 11:00 – 11:20 Uhr (Dauer: 20 min)
Ort Raum 348 (Gebäude 50.34)
Vorheriger Termin Fr 5. Mai 2023
Nächster Termin Fr 26. Mai 2023

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Vortragende(r) Steven Lorenz
Titel Active Learning for experimental exploration
Vortragstyp Proposal
Betreuer(in) Federico Matteucci
Vortragsmodus in Präsenz
Kurzfassung A ranking is the result of running an experiment, a set of encoders is applied to an

experimental condition (dataset, model, tuning, scoring) and are then ranked according to their performance. To draw conclusions about the performance of the encoders for a set of experimental conditions, one can aggregate the rankings into a consensus ranking. (i.e. taking the median rank) The goal of the thesis is to explore the space of consensus rankings and find all possible consensus rankings. However, running an experiment is a very time-consuming task. Therefore we utilize Active Learning, to avoid running unnecessary experiments. In Active Learning, the learner can choose the data it is trained on and achieves greater accuracy with fewer labeled data.

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