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Ronitt Rubinfeld

Ronitt Rubinfeld

D-Index & Metrics

Computer Science

D-Index
49
Citations
9468
World Ranking
5899
National Ranking
2666

Research.com Recognitions

  • 2020 - Fellow of the American Academy of Arts and Sciences
  • 2014 - ACM Fellow For contributions to delegated computation, sublinear time algorithms and property testing.
  • 1996 - Fellow of Alfred P. Sloan Foundation

Overview

Ronitt Rubinfeld is affiliated with the Massachusetts Institute of Technology (MIT) in the United States. Their research primarily spans the field of Computer Science, with significant contributions across various subfields including Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Statistics and Probability, and Control and Systems Engineering.

The scientist's work covers a broad range of main topics, which include:

  • Machine Learning and Algorithms
  • Complexity and Algorithms in Graphs
  • Optimization and Search Problems
  • Markov Chains and Monte Carlo Methods
  • Machine Learning and Data Classification
  • Algorithms and Data Compression
  • Adversarial Robustness in Machine Learning

Ronitt Rubinfeld has published extensively, with a frequent presence in venues such as:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)
  • Algorithmica
  • Warwick Research Archive Portal (University of Warwick)

Recent papers authored or coauthored by Rubinfeld include:

  • Learning-based Support Estimation in Sublinear Time, 2021, arXiv (Cornell University)
  • Properly learning monotone functions via local correction, 2022, 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)
  • Online Page Migration with ML Advice, 2020, arXiv (Cornell University)
  • Towards a Decomposition-Optimal Algorithm for Counting and Sampling Arbitrary Motifs in Sublinear Time, 2021, arXiv (Cornell University)
  • Massively Parallel Algorithms for Small Subgraph Counting, 2022, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Frequent collaborators in Rubinfeld's research include Talya Eden, Amartya Shankha Biswas, Arsen Vasilyan, Slobodan Mitrović, and Piotr Indyk.

The scientist has been recognized with several awards during their career, among them:

  • Fellow of the American Academy of Arts and Sciences, 2020
  • ACM Fellow, 2014, for contributions to delegated computation, sublinear time algorithms and property testing
  • Fellow of Alfred P. Sloan Foundation, 1996

Best Publications

  • Robust Characterizations of Polynomials withApplications to Program Testing

    Ronitt Rubinfeld;Madhu Sudan

  • The Bloomier filter: an efficient data structure for static support lookup tables

    Bernard Chazelle;Joe Kilian;Ronitt Rubinfeld;Ayellet Tal

  • Self-testing/correcting with applications to numerical problems

    M. Blum;M. Luby;R. Rubinfeld

  • Testing that distributions are close

    T. Batu;L. Fortnow;R. Rubinfeld;W.D. Smith

  • On the learnability of discrete distributions

    Michael Kearns;Yishay Mansour;Dana Ron;Ronitt Rubinfeld

  • Testing random variables for independence and identity

    T. Batu;E. Fischer;L. Fortnow;R. Kumar

  • Learning Polynomials with Queries: The Highly Noisy Case

    Oded Goldreich;Ronitt Rubinfeld;Madhu Sudan

  • Monotonicity testing over general poset domains

    Eldar Fischer;Eric Lehman;Ilan Newman;Sofya Raskhodnikova

  • Self-testing/correcting for polynomials and for approximate functions

    Peter Gemmell;Richard Lipton;Ronitt Rubinfeld;Madhu Sudan

  • Tolerant property testing and distance approximation

    Michal Parnas;Dana Ron;Ronitt Rubinfeld

  • The Complexity of Approximating the Entropy

    Tuugkan Batu;Sanjoy Dasgupta;Ravi Kumar;Ronitt Rubinfeld

  • Sublinear Time Algorithms.

    Ronitt Rubinfeld;Asaf Shapira

  • Testing Closeness of Discrete Distributions

    Tuğkan Batu;Lance Fortnow;Ronitt Rubinfeld;Warren D. Smith

  • Approximating the Minimum Spanning Tree Weight in Sublinear Time

    Bernard Chazelle;Ronitt Rubinfeld;Luca Trevisan

  • Testing k-wise and almost k-wise independence

    Noga Alon;Alexandr Andoni;Tali Kaufman;Kevin Matulef

  • Sublinear algorithms for testing monotone and unimodal distributions

    Tugkan Batu;Ravi Kumar;Ronitt Rubinfeld

  • Reconstructing Algebraic Functions from Mixed Data

    Sigal Ar;Richard J. Lipton;Ronitt Rubinfeld;Madhu Sudan

  • Short paths in expander graphs

    J. Kleinberg;R. Rubinfeld

  • Selective private function evaluation with applications to private statistics

    Ran Canetti;Yuval Ishai;Ravi Kumar;Michael K. Reiter

  • Regular ArticleSpot-Checkers☆

    Funda Ergün;Sampath Kannan;S.Ravi Kumar;Ronitt Rubinfeld

  • Fast Local Computation Algorithms

    Ronitt Rubinfeld;Gil Tamir;Shai Vardi;Ning Xie

  • Spot-checkers

    Funda Ergün;Sampath Kannan;S. Ravi Kumar;Ronitt Rubinfeld

  • The complexity of approximating entropy

    Tuǧkan Batu;Sanjoy Dasgupta;Ravi Kumar;Ronitt Rubinfeld

Frequent Co-Authors

Dana Ron
Dana Ron Tel Aviv University
Ravi Kumar
Ravi Kumar Google (United States)
Madhu Sudan
Madhu Sudan Harvard University
Rocco A. Servedio
Rocco A. Servedio Columbia University
Ilias Diakonikolas
Ilias Diakonikolas University of Wisconsin–Madison
Lance Fortnow
Lance Fortnow Illinois Institute of Technology
Christian Sohler
Christian Sohler University of Cologne
Artur Czumaj
Artur Czumaj University of Warwick
Michael Luby
Michael Luby BitRipple

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