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Termin (Alle Termine)
Datum Freitag, 2. Juni 2023
Uhrzeit 11:00 – 11:20 Uhr (Dauer: 20 min)
Ort Raum 348 (Gebäude 50.34)
Vorheriger Termin Fr 26. Mai 2023
Nächster Termin Fr 9. Juni 2023

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Vortragende(r) Simon Benedict
Titel Online Nyström MMD Approximation
Vortragstyp Proposal
Betreuer(in) Florian Kalinke
Vortragsmodus in Präsenz
Kurzfassung In data analysis, the ability to detect and understand critical shifts in information patterns holds immense significance. Whether it is monitoring real-time network traffic, identifying anomalies in financial markets, or tracking fluctuations in climate data, the ability to swiftly identify change points is crucial for effective decision-making. Since the default implementation of MMD is quadratic the algorithms to enable this however tend to exceed runtime limits for certain contexts, such as those where the speed and volume of incoming data is relatively high. In continuation of recent developments in change point detection optimization through estimators, notably RADMAN, we propose to integrate the “Nyström” estimator into a similar context of exponential bucketing to improve on this matter. This thesis will focus on the concept, the implementation and testing of this construct and its comparison to other recent approaches.
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