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R. Mazumder

80 papers hereh-index 265.9k citations98 works total

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

author position
  • first author14
  • middle author17
  • last author49

Across the 80 of 80 papers where every author was matched, so the position is known.

fields
  • stat.ML21
  • cs.LG19
  • math.OC12
  • stat.ME10
  • stat.CO8
  • math.ST4
same name
  • R. Mazumder — 7 papers, h 15
  • R. Mazumder — 2 papers, h 16
  • R. Mazumder — 2 papers, h 13
  • R. Mazumder — 2 papers, h 13
  • R. Mazumder — 2 papers, h 6
  • R. Mazumder — 1 paper, h 31

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
20082026
most citedMatrix Completion and Low-Rank SVD via Fast Alternating Least Squares

307 citations · 693 across the 70 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

stat.ME2017★ 3 cited

Mining Events with Declassified Diplomatic Documents

Yuanjun Gao, Jack Goetz, Rahul Mazumder +1

Since 1973 the State Department has been using electronic records systems to preserve classified communications. Recently, approximately 1.9 million of these records from 1973-77 h…

math.OC2017★ 1 cited

Sparse principal component analysis and its l1​-relaxation

Santanu S. Dey, Rahul Mazumder, Marco Molinaro +1

Principal component analysis (PCA) is one of the most widely used dimensionality reduction methods in scientific data analysis. In many applications, for additional interpretabilit…

stat.ME2017★ 13 cited

The Trimmed Lasso: Sparsity and Robustness

Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder

Nonconvex penalty methods for sparse modeling in linear regression have been a topic of fervent interest in recent years. Herein, we study a family of nonconvex penalty functions t…

stat.ME2017★ 9 cited

Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is low

Rahul Mazumder, Peter Radchenko, Antoine Dedieu

We study a seemingly unexpected and relatively less understood overfitting aspect of a fundamental tool in sparse linear modeling - best subset selection, which minimizes the resid…

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