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A. Bandeira

77 papers hereh-index 436.4k citations115 works total

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

author position
  • sole author2
  • first author40
  • middle author21
  • last author13

Across the 76 of 77 papers where every author was matched, so the position is known.

fields
  • math.OC14
  • math.ST12
  • cs.IT9
  • math.FA9
  • math.PR9
  • cs.DS7
same name
  • A. Bandeira — 1 paper, h 3

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
20112026
most citedSharp nonasymptotic bounds on the norm of random matrices with independent entries

202 citations · 1.3k across the 61 of their papers we have counts for

collaborators
Showing 2012Show all

4 papers · 1 filter

cs.IT2012

Phase retrieval with polarization

Boris Alexeev, Afonso S. Bandeira, Matthew Fickus +1

In many areas of imaging science, it is difficult to measure the phase of linear measurements. As such, one often wishes to reconstruct a signal from intensity measurements, that i…

math.SP2012★ 5 cited

A Cheeger Inequality for the Graph Connection Laplacian

Afonso S. Bandeira, Amit Singer, Daniel A. Spielman

The O(d) Synchronization problem consists of estimating a set of unknown orthogonal transformations O_i from noisy measurements of a subset of the pairwise ratios O_iO_j^{-1}. We f…

math.FA2012★ 166 cited

Certifying the restricted isometry property is hard

Afonso S. Bandeira, Edgar Dobriban, Dustin G. Mixon +1

This paper is concerned with an important matrix condition in compressed sensing known as the restricted isometry property (RIP). We demonstrate that testing whether a matrix satis…

math.FA2012★ 9 cited

The road to deterministic matrices with the restricted isometry property

Afonso S. Bandeira, Matthew Fickus, Dustin G. Mixon +1

The restricted isometry property (RIP) is a well-known matrix condition that provides state-of-the-art reconstruction guarantees for compressed sensing. While random matrices are k…

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