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Title | Fanny Yang - |
Description | Fanny Yang Research Group Personal Contact My professional information has moved to my group website PC: ETHZ / Giulia Marthaler For a long and detailed v |
Keywords | N/A |
WebSite | fanny-yang.de |
Host IP | 5.45.108.250 |
Location | Germany |
Euro€1,653
Zuletzt aktualisiert: 2022-07-03 09:39:13
fanny-yang.de hat Semrush globalen Rang von 17,691,270. fanny-yang.de hat einen geschätzten Wert von € 1,653, basierend auf seinen geschätzten Werbeeinnahmen. fanny-yang.de empfängt jeden Tag ungefähr 551 einzelne Besucher. Sein Webserver befindet sich in Germany mit der IP-Adresse 5.45.108.250. Laut SiteAdvisor ist fanny-yang.de sicher zu besuchen. |
Kauf-/Verkaufswert | Euro€1,653 |
Tägliche Werbeeinnahmen | Euro€44,631 |
Monatlicher Anzeigenumsatz | Euro€14,877 |
Jährliche Werbeeinnahmen | Euro€1,102 |
Tägliche eindeutige Besucher | 551 |
Hinweis: Alle Traffic- und Einnahmenwerte sind Schätzungen. |
Host | Type | TTL | Data |
fanny-yang.de. | A | 7200 | IP: 5.45.108.250 |
fanny-yang.de. | NS | 7200 | NS Record: second-dns.netcup.net. |
fanny-yang.de. | NS | 7200 | NS Record: root-dns.netcup.net. |
fanny-yang.de. | NS | 7200 | NS Record: third-dns.netcup.net. |
fanny-yang.de. | MX | 7200 | MX Record: 10 mail.fanny-yang.de. |
Fanny Yang Research Group Personal Contact My professional information has moved to my group website PC: ETHZ / Giulia Marthaler For a long and detailed version of my CV click here fanny-yang (at) berkeley.edu I am an Assistant Professor in the Computer Science Department (D-INFK) at ETH Zurich. Previously I was a postdoctoral Scholar at Stanford University working with John Duchi and Percy Liang and a Junior Fellow at the Institute for Theoretical Studies at ETH Zurich working with Nicolai Meinshausen . Before that, I was a PhD student at the EECS department of UC Berkeley advised by Martin Wainwright . I’m generally interested in theoretically understanding and developing tools in machine learning and statistics that work well. Currently I am particularly curious about gaining theoretical understanding for the generalization properties of overparameterized models for high-dimensional data (motivated by neural networks) as well as a plethora of questions related to obtaining more |
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