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Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix


Jun 10, 2021
Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher

* ICML 2021 

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DRIVE: One-bit Distributed Mean Estimation


Jun 02, 2021
Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher


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How to send a real number using a single bit (and some shared randomness)


Oct 08, 2020
Ran Ben-Basat, Michael Mitzenmacher, Shay Vargaftik


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Queues with Small Advice


Jun 27, 2020
Michael Mitzenmacher

* 16 pages, draft version, to be submitted, subject to cahnge 

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Partitioned Learned Bloom Filter


Jun 05, 2020
Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher

* 13 pages, 3 figures 

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Optimal Learning of Joint Alignments with a Faulty Oracle


Sep 21, 2019
Kasper Green Larsen, Michael Mitzenmacher, Charalampos E. Tsourakakis

* 10 pages 

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The Supermarket Model with Known and Predicted Service Times


May 23, 2019
Michael Mitzenmacher

* 14 pages, draft version, to be submitted, later improvements possible 

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Online Pandora's Boxes and Bandits


Jan 30, 2019
Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher


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A Model for Learned Bloom Filters, and Optimizing by Sandwiching


Jan 03, 2019
Michael Mitzenmacher

* 12 pages; the complete version of the paper that appears in NIPS 2018, including addendum on learned Bloomier filters. arXiv admin note: substantial text overlap with arXiv:1802.00884, arXiv:1803.01474 

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Predicting Positive and Negative Links with Noisy Queries: Theory & Practice


Aug 07, 2018
Charalampos E. Tsourakakis, Michael Mitzenmacher, Kasper Green Larsen, Jarosław Błasiok, Ben Lawson, Preetum Nakkiran, Vasileios Nakos

* arXiv admin note: text overlap with arXiv:1609.00750 

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2-Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search


Feb 21, 2016
Ping Li, Michael Mitzenmacher, Anshumali Shrivastava

* arXiv admin note: text overlap with arXiv:1403.8144 

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Theoretical Foundations of Equitability and the Maximal Information Coefficient


May 12, 2015
Yakir A. Reshef, David N. Reshef, Pardis C. Sabeti, Michael Mitzenmacher

* 46 pages, 3 figures, 2 tables. This paper has been subsumed by arXiv:1505.02213 and arXiv:1505.02212. Please cite those papers instead 

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Coding for Random Projections and Approximate Near Neighbor Search


Mar 31, 2014
Ping Li, Michael Mitzenmacher, Anshumali Shrivastava


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Equitability Analysis of the Maximal Information Coefficient, with Comparisons


Aug 14, 2013
David Reshef, Yakir Reshef, Michael Mitzenmacher, Pardis Sabeti

* 22 pages, 9 figures 

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Coding for Random Projections


Aug 09, 2013
Ping Li, Michael Mitzenmacher, Anshumali Shrivastava


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