Review of dependency estimation with focus on data efficiency: Unterschied zwischen den Versionen
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|vortragstyp=Proposal | |vortragstyp=Proposal | ||
|betreuer=Bela Böhnke | |betreuer=Bela Böhnke | ||
|termin=Institutsseminar/2022-01-14 | |termin=Institutsseminar/2022-01-14 Zusatztermin | ||
|kurzfassung=In our data-driven world, where tons of data are collected, dependency estimation is important to get more insights into our data. Many dependency estimation algorithms are hard to use in a real-world setting. In this study, I will do a comparison of different state-of-the-art dependency estimation algorithms. For comparison, a list of different criteria is used and the focus of this study is on data efficiency and uncertainty of the dependency estimation algorithms. The comparison includes a theoretical analysis and a variety of different experiments with an implementation of the dependency estimation algorithm that performed well in the theoretical analysis. | |kurzfassung=In our data-driven world, where tons of data are collected, dependency estimation is important to get more insights into our data. Many dependency estimation algorithms are hard to use in a real-world setting. In this study, I will do a comparison of different state-of-the-art dependency estimation algorithms. For comparison, a list of different criteria is used and the focus of this study is on data efficiency and uncertainty of the dependency estimation algorithms. The comparison includes a theoretical analysis and a variety of different experiments with an implementation of the dependency estimation algorithm that performed well in the theoretical analysis. | ||
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Version vom 5. Januar 2022, 16:08 Uhr
Vortragende(r) | Maximilian Georg | |
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Vortragstyp | Proposal | |
Betreuer(in) | Bela Böhnke | |
Termin | [[Institutsseminar/2022-01-14 Zusatztermin|]] | |
Vortragsmodus | ||
Kurzfassung | In our data-driven world, where tons of data are collected, dependency estimation is important to get more insights into our data. Many dependency estimation algorithms are hard to use in a real-world setting. In this study, I will do a comparison of different state-of-the-art dependency estimation algorithms. For comparison, a list of different criteria is used and the focus of this study is on data efficiency and uncertainty of the dependency estimation algorithms. The comparison includes a theoretical analysis and a variety of different experiments with an implementation of the dependency estimation algorithm that performed well in the theoretical analysis. |