• Publications
  • Influence
Fairness through awareness
TLDR
We study fairness in classification, where the goal is to prevent discrimination against individuals based on their membership in some group, while maintaining utility for the classifier (the university). Expand
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Undirected connectivity in log-space
  • O. Reingold
  • Mathematics, Computer Science
  • JACM
  • 1 September 2008
TLDR
We present a deterministic, log-space algorithm that solves st-connectivity in undirected graphs with space complexity log4/3(ṡ) . Expand
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Number-theoretic constructions of efficient pseudo-random functions
  • M. Naor, O. Reingold
  • Mathematics, Computer Science
  • Proceedings 38th Annual Symposium on Foundations…
  • 19 October 1997
TLDR
We describe efficient constructions of pseudo-random functions such that computing their value at any given point involves two multiple products. Expand
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Priced Oblivious Transfer: How to Sell Digital Goods
TLDR
We propose solutions which allow a buyer to purchase digital goods from a vendor without letting the vendor learn what, and to the extent possible also when and how much, it is buying. Expand
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An optimal bifactor approximation algorithm for the metric uncapacitated facility location problem
We consider the metric uncapacitated facility location problem(UFL). In this paper we modify the (1 + 2/e)-approximation algorithm of Chudak and Shmoys to obtain a new (1.6774,1.3738)approximationExpand
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Keyword Search and Oblivious Pseudorandom Functions
TLDR
We study the problem of privacy-preserving access to a database. Expand
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Undirected ST-connectivity in log-space
  • O. Reingold
  • Computer Science, Mathematics
  • STOC '05
  • 22 May 2005
TLDR
We present a deterministic, log-space algorithm that solves st-connectivity in undirected graphs with O(log n log log log n)-space complexity. Expand
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Preserving Statistical Validity in Adaptive Data Analysis
TLDR
We propose a principled study of how to guarantee the validity of statistical inference in adaptive data analysis. Expand
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Distributed Pseudo-random Functions and KDCs
TLDR
This work describes schemes for distributing between n servers the evaluation of a function which is an approximation to a random function, such that only authorized subsets of servers are able to compute the function. Expand
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Generalization in Adaptive Data Analysis and Holdout Reuse
TLDR
We give an algorithm that enables the validation of a large number of adaptively chosen hypotheses, while provably avoiding overfitting to the holdout set. Expand
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