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in computer science from the Massachusetts Institute of Technology in 2017, under the supervision of Piotr Indyk. Sepideh Mahabadi. Toyota Technological Institute at Chicago (TTIC) Verified email at ttic.edu - Homepage. S Mahabadi, K Makarychev, Y Makarychev, I Razenshteyn. Sepideh Mahabadi. Toyota Technological Institute at Chicago.
Facebook gives people the power to share 2020/04/29: Sepideh Mahabadi (TTIC). posted Apr 29, 2020, 1:34 PM by Gautam Kamath [ updated May 13, 2020, 1:58 PM by Alice Bob ] Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. Sepideh Mahabadi, Piotr Indyk, Shayan Oveis Gharan, Alireza Rezaei. Authors. Sariel Har-Peled, Sepideh Mahabadi.
She received her Ph.D. from MIT, where she was advised by Piotr Indyk.
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WEB: Event Website. SHARE: (Click “Event Website” above to access the zoom link.) 2020-07-07 Talk: Sepideh Mahabadi: Composable Core-sets for Diversity and Coverage Maximization, and Its Application in Diverse Near Neighbor Problem. Speaker: Sepideh Mahabadi , MIT Date: Wednesday, May 07, 2014 Time: 4:00 PM to 5:00 PM Public: Yes Location: 32-G575 Event Type: Sepideh Mahabadi (Toyota Technological Institute at Chicago) Ruta Mehta (University of Illinois, Urbana-Champaign) Raghu Meka (University of California, Los Angeles) Dor Minzer (Massachusetts Institute of Technology) Jesper Nederlof (Utrecht University) Jelani Nelson (University of California, Berkeley) Sasho Nikolov (University of Toronto) Sepideh Mahabadi Submitted to the Department of Electrical Engineering and Computer Science on May 22, 2013, in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering Abstract This thesis investigates two variants of the approximate nearest neighbor problem.
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PODS (2014), pp.
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2020/04/29: Sepideh Mahabadi (TTIC). posted Apr 29, 2020, 1:34 PM by Gautam Kamath [ updated May 13, 2020, 1:58 PM by Alice Bob ]
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. Sepideh Mahabadi, Piotr Indyk, Shayan Oveis Gharan, Alireza Rezaei.
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MathSciNet.
(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.
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%0 Conference Paper %T Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm %A Sepideh Mahabadi %A Piotr Indyk %A Shayan Oveis Gharan %A Alireza Rezaei %B Proceedings of the 36th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2019 %E Kamalika Chaudhuri %E Ruslan Salakhutdinov %F pmlr-v97-mahabadi19a %I PMLR %P 4254 In Spring Quarter 2021, Sepideh Mahabadi will be teaching a new course, Special Topics: Algorithms for Massive Data. 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. Sepideh Mahabadi* 1 Ali Vakilian* 2 Abstract We give a local search based algorithm for k-median and k-means (and more generally for any k-clustering with ‘ pnorm cost function) from the perspective of individual fairness.