Corinna Cortes | |
|---|---|
| Born | March 31, 1961 |
| Alma mater | University of Copenhagen (MS) University of Rochester (PhD) |
| Known for | Support vector machines MNIST database |
| Awards | Paris Kanellakis Award (2008) ACM Fellow (2023) |
| Scientific career | |
| Fields | Machine learning Data mining[1] |
| Institutions | Google UCPH Department of Computer Science AT&T Bell Labs Bell Labs |
| Thesis | Prediction of generalization ability in learning machines (1994) |
| Doctoral advisor | Randal C. Nelson[2] |
| Website | research |
Corinna Cortes (born 31 March 1961) is a Danish computer scientist known for her contributions to machine learning. She is a Vice President at Google Research in New York City.[3] Cortes is an ACM Fellow and a recipient of the Paris Kanellakis Award for her work on theoretical foundations of support vector machines.[4][5][3][6]
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Transcription
Early life and education
Corinna Cortes was born in 1961 in Denmark.[citation needed] Cortes received her Master of Science degree in physics from University of Copenhagen in 1989.[3] She received her PhD in computer science from the University of Rochester in 1993 for research supervised by Randal C. Nelson.[2]
Career and research
Cortes joined AT&T Bell Labs as a researcher in 1993. Since 2003, she has served as Vice President of Google Research, New York City,[3] and since 2011, as adjunct professor at the UCPH Department of Computer Science.[7] She is serves as an editorial board member of the journal Machine Learning.[8]
Cortes' research covers a wide range of topics in machine learning, including support vector machines (SVM) and data mining. SVM is one of the most frequently used algorithms in machine learning, which is used in many practical applications, including medical diagnosis and weather forecasting.[4] At AT&T, Cortes was a contributor to the design of Hancock programming language.[9]
Awards and honors
In 2008, she jointly with Vladimir Vapnik received the Paris Kanellakis Award for the development of a highly effective algorithm for supervised learning known as support vector machines (SVM).[10] She was named an ACM Fellow in 2023 for theoretical and practical contributions to machine learning, industrial leadership and service to the field.[11]
Personal life
Corinna has two children and is also a competitive runner.[3]
References
- ^ Corinna Cortes publications indexed by Google Scholar
- ^ a b Cortes, Corinna (1993). Prediction of generalization ability in learning machines. rochester.edu (PhD thesis). University of Rochester. hdl:1802/811. OCLC 31469473. ProQuest 304147134.
- ^ a b c d e research
.google /people /author121 - ^ a b "ACM Awards Recognize Innovators in Computer Science Who Solve Real World Problems". Association for Computing Machinery. Archived from the original on 15 April 2012. Retrieved 8 November 2011.
- ^ Corinna Cortes at DBLP Bibliography Server
- ^ Corinna Cortes author profile page at the ACM Digital Library
- ^ "Miniportræt: Corinna Cortes" (in Danish). University of Copenhagen, Department of Computer Science. 2014-09-10. Retrieved 2 April 2021.[dead link]
- ^ "Machine Learning - Editorial Board". Springer. Retrieved 8 November 2011.
- ^ Cortes, Corinna; Fisher, Kathleen; Pregibon, Daryl; Rogers, Anne; Smith, Frederick (2004-03-01). "Hancock: A language for analyzing transactional data streams". ACM Transactions on Programming Languages and Systems. 26 (2): 301–338. doi:10.1145/973097.973100. ISSN 0164-0925. S2CID 12915177.
- ^ Cortes, Corinna; Vladimir Vapnik (1995). "Support-Vector Networks". Machine Learning. 20 (3): 273–297. doi:10.1007/BF00994018.
- ^ Anon (2023). "Global Computing Association Names 57 Fellows for Outstanding Contributions That Propel Technology Today". acm.org. Archived from the original on 2023-01-18.
This page was last edited on 3 March 2024, at 04:44