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Maxim Panov

Technology Innovation Institute

30 papers hereh-index 191.1k citations59 works total

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

author position
  • first author2
  • middle author12
  • last author16

Across the 30 of 30 papers where every author was matched, so the position is known.

fields
  • stat.ML15
  • cs.LG6
  • math.ST4
  • cs.CV2
  • cs.CL1
  • cs.MS1
affiliations
  • Technology Innovation Institute
Homepage
same name
  • Maxim Panov — 20 papers, h 8
  • Maxim Panov — 13 papers, h 6
  • Maxim Panov — 1 paper

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
20132025
most citedDropout-based Active Learning for Regression

43 citations · 153 across the 27 of their papers we have counts for

collaborators
Showing math.STShow all

4 papers · 1 filter

math.ST2021

Assigning Topics to Documents by Successive Projections

Olga Klopp, Maxim Panov, Suzanne Sigalla +1

Topic models provide a useful tool to organize and understand the structure of large corpora of text documents, in particular, to discover hidden thematic structure. Clustering doc…

math.ST2019★ 6 cited

Accuracy of Gaussian approximation in nonparametric Bernstein -- von Mises Theorem

Vladimir Spokoiny, Maxim Panov

The prominent Bernstein -- von Mises (BvM) result claims that the posterior distribution after centering by the efficient estimator and standardizing by the square root of the tota…

math.ST2017★ 15 cited

Consistent Estimation of Mixed Memberships with Successive Projections

Maxim Panov, Konstantin Slavnov, Roman Ushakov

This paper considers the parameter estimation problem in Mixed Membership Stochastic Block Model (MMSB), which is a quite general instance of random graph model allowing for overla…

math.ST2013★ 35 cited

Finite Sample Bernstein -- von Mises Theorem for Semiparametric Problems

Maxim Panov, Vladimir Spokoiny

The classical parametric and semiparametric Bernstein -- von Mises (BvM) results are reconsidered in a non-classical setup allowing finite samples and model misspecification. In th…

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