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Aaron Roth

University of Pennsylvania

109 papers hereh-index 6124.3k citations197 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author5
  • middle author59
  • last author43

Across the 108 of 109 papers where every author was matched, so the position is known.

fields
  • cs.LG47
  • cs.GT26
  • cs.DS23
  • cs.CR4
  • cs.PL2
  • stat.ML2
affiliations
  • University of Pennsylvania
Homepage
same name
  • Aaron Roth — 16 papers, h 8
  • Aaron Roth — 9 papers, h 4
  • Aaron Roth — 7 papers, h 3
  • Aaron Roth — 5 papers, h 3
  • Aaron Roth — 5 papers, h 1
  • Aaron Roth — 4 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092023
most citedPreventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

381 citations · 2.3k across the 89 of their papers we have counts for

collaborators
Showing 2011 · cs.DSShow all

4 papers · 2 filters

cs.DS2011

Fast Private Data Release Algorithms for Sparse Queries

Avrim Blum, Aaron Roth

We revisit the problem of accurately answering large classes of statistical queries while preserving differential privacy. Previous approaches to this problem have either been very…

cs.DS2011★ 77 cited

Beating Randomized Response on Incoherent Matrices

Moritz Hardt, Aaron Roth

Computing accurate low rank approximations of large matrices is a fundamental data mining task. In many applications however the matrix contains sensitive information about individ…

cs.DS2011★ 1 cited

A Learning Theory Approach to Non-Interactive Database Privacy

Avrim Blum, Katrina Ligett, Aaron Roth

In this paper we demonstrate that, ignoring computational constraints, it is possible to privately release synthetic databases that are useful for large classes of queries -- much…

cs.DS2011

Iterative Constructions and Private Data Release

Anupam Gupta, Aaron Roth, Jonathan Ullman

In this paper we study the problem of approximately releasing the cut function of a graph while preserving differential privacy, and give new algorithms (and new analyses of existi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.