Sepideh Mahabadi is a research assistant professor at the Toyota Technological Institute at Chicago (TTIC). She received her Ph.D. from MIT, where she was advised by Piotr Indyk. For a year, she was a postdoctoral research scientist at Simons Collaboration on …

Sepideh Mahabadi · Piotr Indyk · Shayan Oveis Gharan · Alireza Rezaei 2019 Poster: Scalable Fair Clustering » Arturs Backurs · Piotr Indyk · Krzysztof Onak · Baruch Schieber · Ali Vakilian · Tal Wagner 2019 Oral: Scalable Fair Clustering »

Sepideh Mahabadi, Konstantin Makarychev, Yury Makarychev, Ilya Razenshteyn, Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extensions, STOC 2018. (pdf, slides) Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee, Set Cover in Sub-linear Time, SODA 2018. Sepideh Mahabadi received her PhD in Computer Science from MIT in 2017, where she was part of the Theory of Computation group in CSAIL. Before joining TTIC, for a year she was a postdoctoral research scientist at Simons Collaboration on Algorithms and Geometry hosted at Columbia University. Sepideh Mahabadi, Ilya Razenshteyn, David Woodru , Samson Zhou, Non-Adaptive Adap-tive Sampling on Turnstile Streams.

Sepideh mahabadi

Massachusetts Institute of Technology 2017 UnitedStates. Dissertation: Sub-linear Algorithms for Massive Data Problems. Apr 23, 2020 Non-Adaptive Adaptive Sampling on Turnstile Streams. Authors:Sepideh Mahabadi, Ilya Razenshteyn, David P. Woodruff, Samson Zhou. Individual Fairness for k-Clustering. Sepideh Mahabadi · Ali Vakilian.

Join Facebook to connect with Sepideh Mahabadi and others you may know. Facebook gives people the power to share and makes the world more open and connected. 2021-02-04 Title: Non-Adaptive Adaptive Sampling in Turnstile Streams Abstract: Adaptive sampling is a useful algorithmic tool for data summarization problems in the cl 2019-05-24 Sepideh Mahabadi is a research assistant professor at the Toyota Technological Institute at Chicago (TTIC).

Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. Sepideh Mahabadi, Piotr Indyk, Shayan Oveis Gharan, Alireza Rezaei.

This course will cover the theoretical aspects of computation over massive data. While classical algorithms can be too slow, or require too much space on big data, in this course students will focus on designing algorithms that are specifically tailored for large datasets. View Sepideh Mahabadi’s profile on LinkedIn, the world’s largest professional community. Sepideh has 1 job listed on their profile.

Sepideh Mahabadi is a postdoctoral research scientist with an appointment at the Simons Collaboration on Algorithms and Geometry based at Columbia University, working with Alexandr Andoni. She received her Ph.D. in computer science from the Massachusetts Institute of Technology in 2017, under the supervision of Piotr Indyk.

View the profiles of people named Sepideh Mahabadi. Join Facebook to connect with Sepideh Mahabadi and others you may know. Facebook gives people the Sepideh Mahabadi's 24 research works with 180 citations and 395 reads, including: Streaming Complexity of SVMs Sepideh Mahabadi is a research assistant professor at the Toyota Technological Institute at Chicago (TTIC). She received her Ph.D. from MIT, where she was advised by Piotr Indyk. For a year, she was a postdoctoral research scientist at Simons Collaboration on Algorithms and Geometry based at Columbia University.

Toyota Technological Institute at Chicago. Assistant Professor. Sepideh is Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC).
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In 2013 she received her M.Sc. and in 2017 her PhD from the MIT. When she was 18 years old she made history at the International Olympiad… Read Sepideh Mahabadi's latest research, browse their coauthor's research, and play around with their algorithms Sepideh Mahabadi.

from MIT, where she was advised by Piotr Indyk. For a year, she was a postdoctoral research scientist at Simons Collaboration on Algorithms and Geometry based at Columbia University. Sepideh Mahabadi: Composable Core-sets for Diversity and Coverage Maximization, and Its Application in Diverse Near Neighbor Problem Wednesday, May 7, 2014 - 4:00pm to 5:00pm Location: Sepideh Mahabadi is a research assistant professor at the Toyota Technological Institute at Chicago (TTIC). She received her Ph.D.
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Reminder Subject: TALK: THESIS DEFENSE: Sepideh Mahabadi: Sub-linear Algorithms for Massive Data Problems Abstract: The recent availability of massive data sets has had a significant impact on the design of algorithms. This has led to the emergence of new computational models that capture various aspects of massive data computation.

More precisely, for a point xin a point set Pof size n, let r(x) be the minimum radius such that the ball of radius Sepideh Mahabadi is on Facebook. Join Facebook to connect with Sepideh Mahabadi and others you may know. Facebook gives people the power to share and makes the world more open and connected.

Sepideh Mahabadi is a postdoctoral research scientist with an appointment at the Simons Collaboration on Algorithms and Geometry based at Columbia University. More articles on Iranian successes in science competitions Sources: Press TV, MIT, Simons Foundation, stats.ioiinformatics.org (IOI 2007)

Most frequent co-Author Sepideh Mahabadi's 26 research works with 187 citations and 461 reads, including: Sampling a Near Neighbor in High Dimensions -- Who is the Fairest of Them All? Sepideh Mahabadi is Research Assistant Professor at Toyota Technological Institute at Chicago. View Sepideh Mahabadi’s professional profile on Relationship Science, the database of decision makers. View the profiles of people named Sepideh Mahabadi. Join Facebook to connect with Sepideh Mahabadi and others you may know. Facebook gives people the Sepideh Mahabadi's 24 research works with 180 citations and 395 reads, including: Streaming Complexity of SVMs Sepideh Mahabadi is a research assistant professor at the Toyota Technological Institute at Chicago (TTIC).