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Marco Perone-Pacifico

dblp:81/8315 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Learning theory · 67% Representation and self-supervised learning · 33%
Theoretical computer science
1 paper
Algorithms and data structures · 50% Computational geometry · 50%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Representation and self-supervised learning › representation learning › dimensionality reduction › manifold learning
manifold fitting		 0.112012
Minimax Manifold Estimation · J. Mach. Learn. Res. 2012
Machine learning › Learning theory › statistical estimation › minimax estimation
minimax rates		 0.112012
Minimax Manifold Estimation · J. Mach. Learn. Res. 2012
Machine learning › Learning theory
statistical estimation		 0.112012
Minimax Manifold Estimation · J. Mach. Learn. Res. 2012
Computational geometry › geometric modeling and processing › point cloud analysis › geometric reconstruction
manifold estimation		 0.112012
Minimax Manifold Estimation · J. Mach. Learn. Res. 2012
Algorithms and data structures › numerical linear algebra › dimensionality reduction › nonlinear dimensionality reduction
manifold learning		 0.112012
Minimax Manifold Estimation · J. Mach. Learn. Res. 2012

Methods — techniques the papers use, named apart from their topics

minimax analysis · 0.3manifold estimation · 0.3
YearPublicationVenuePosition
2012 Minimax Manifold Estimation
Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry A. Wasserman
 J. Mach. Learn. Res.2