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Real-time recommendation of diverse related articles. In Proceedings of the 22nd international conference on World Wide Web (WWW '13). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 1-12. 2014-10-12 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

PODS (2014), pp. 6 days ago Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri: Sampling a Near Neighbor in High Dimensions Sepideh Mahabadi received 2011 her B.Sc. in Computer Engineering from the Sharif University of Technology, Iran. That year she moved to the United States to Ismael Bakhshi, fackföreningsaktivist; Sepideh Gholian, journalist Baktash Abtin, Resa Khandan Mahabadi och Keyvan Bazhan – alla Sepideh Amirpour. Industrial PhD Candidate at CEVT (China Euro Vehicle Technology AB), Chalmers University of Technology. Göteborgsområdet.

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.

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She received her PhD in Computer Science, at the Theory of Computation Group at CSAIL, MIT, where she had Prof. Piotr Indyk as her advisor.

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Sepideh Mahabadi. Toyota Technological Institute at Chicago (TTIC) Verified email at ttic.edu - Homepage. P Indyk, S Mahabadi, R Rubinfeld, A Vakilian, A Yodpinyanee. Read Sepideh Mahabadi's latest research, browse their coauthor's research, and play around with their algorithms 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. Search for Sepideh Mahabadi's work. Search Search. Home Sepideh Mahabadi.

Search is often formalized as the (approximate) nearest neighbor problem. Sepideh Mahabadi Research Assistant Professor Toyota Technological Institute at Chicago (TTIC) WHEN: September 18, 2020 @ 10:00 am - 11:00 am Sepideh Mahabadi Ali Vakiliany Abstract We give a local search based algorithm for k-median and k-means (and more generally for any k-clustering with ‘ p norm cost function) from the perspective of individual fairness. More precisely, for a point xin a point set Pof size n, let r(x) be the minimum radius such that the 2020-07-07 · We study the space complexity of solving the bias-regularized SVM problem in the streaming model.
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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's 24 research works with 180 citations and 395 reads, including: Streaming Complexity of SVMs Affiliation: CSAIL MIT 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) Sepideh Mahabadi is a research assistant professor at the Toyota Technological Institute at Chicago (TTIC).

Individual Fairness for k-Clustering. Sepideh Mahabadi · Ali Vakilian. Tue Jul 14 07:00 AM -- 07:45 AM & Tue Jul 14 06:00 PM -- 06:45 PM (PDT) @ Virtual Sampling a Near Neighbor in High Dimensions--Who is the Fairest of Them All? ( pdf); Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei, Research Assistant Professor at TTIC. PhD in (Theoretical) Computer Science from MIT. Chicago.
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She received her PhD 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. Title: Non-Adaptive Adaptive Sampling in Turnstile Streams Abstract: Adaptive sampling is a useful algorithmic tool for data summarization problems in the cl Sepideh Mahabadi; Affiliations. Massachusetts Institute of Technology (5) Carnegie Mellon University (2) Microsoft Research (2) University of Washington, Seattle (2) 2021-02-04 · 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.

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For a year, she was a postdoctoral research scientist at Simons Collaboration on Algorithms and Geometry based at Columbia University. %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. 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.

Sepideh is Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC). She received her PhD in Computer Science, at the Theory of Computation Group at CSAIL, MIT, where she had Prof. Piotr Indyk as her advisor. 2013-11-22 · Sepideh Mahabadi received 2011 her B.Sc. in Computer Engineering from the Sharif University of Technology, Iran.