Mario23: Started an article about ewin tang.
Ewin Tang (*2000) is an US-american [[Computer Science|computer scientist]]. She did her Bachelor at [[University of Texas at Austin]] (advisor: [[Scott Aaronson]]), and is currently a PhD student at [[University of Washington]].
In 2018, at the age of 18, Tang became widely recognized<ref>[http://bit.ly/2MNGaGj Scott Aaronson, Customers who liked this quantum recommendation engine might also like its dequantization]</ref><ref>[http://bit.ly/2EG4191 Quanta magazin: Major Quantum Computing Advance Made Obsolete by Teenager]</ref> for discovering a quantum-inspired fast classical algorithm various machine learning problems, such as the [[Recommender system|recommendation system]]<ref>[http://bit.ly/2MNjeXE Tang, Ewin. "A quantum-inspired classical algorithm for recommendation systems." arXiv:1807.04271 (2018).]</ref>, [[Principal component analysis]]<ref>[http://bit.ly/2DTNgq5 Tang, Ewin. "Quantum-inspired classical algorithms for principal component analysis and supervised clustering." arXiv:1811.00414 (2018).]</ref> and [[Invertible matrix|matrix inversion]] for low-rank matrices (together with [[Seth Lloyd]])<ref>[http://bit.ly/2ML5aOi Gilyén, András, Seth Lloyd, and Ewin Tang. "Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension." arXiv:1811.04909 (2018).]</ref>. These [[quantum machine learning]] algorithms have been among the leading candidates for practically useful and potential near-term applications of [[quantum computers]].
She has been selected at [[Forbes]] list of [[Forbes 30 Under 30|30 Under 30]] in 2019.
== Links ==
[https://ewintang.com/ Ewin Tang's website]
== References ==
<references />
In 2018, at the age of 18, Tang became widely recognized<ref>[http://bit.ly/2MNGaGj Scott Aaronson, Customers who liked this quantum recommendation engine might also like its dequantization]</ref><ref>[http://bit.ly/2EG4191 Quanta magazin: Major Quantum Computing Advance Made Obsolete by Teenager]</ref> for discovering a quantum-inspired fast classical algorithm various machine learning problems, such as the [[Recommender system|recommendation system]]<ref>[http://bit.ly/2MNjeXE Tang, Ewin. "A quantum-inspired classical algorithm for recommendation systems." arXiv:1807.04271 (2018).]</ref>, [[Principal component analysis]]<ref>[http://bit.ly/2DTNgq5 Tang, Ewin. "Quantum-inspired classical algorithms for principal component analysis and supervised clustering." arXiv:1811.00414 (2018).]</ref> and [[Invertible matrix|matrix inversion]] for low-rank matrices (together with [[Seth Lloyd]])<ref>[http://bit.ly/2ML5aOi Gilyén, András, Seth Lloyd, and Ewin Tang. "Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension." arXiv:1811.04909 (2018).]</ref>. These [[quantum machine learning]] algorithms have been among the leading candidates for practically useful and potential near-term applications of [[quantum computers]].
She has been selected at [[Forbes]] list of [[Forbes 30 Under 30|30 Under 30]] in 2019.
== Links ==
[https://ewintang.com/ Ewin Tang's website]
== References ==
<references />
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