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Yaroslav Kurylev

dblp:01/9302 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—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
Representation and self-supervised learning · 100%
Theoretical computer science
1 paper
Computational geometry · 50% Information theory · 50%

Topics — the 4 heaviest of 5, 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		 0.312018
Fitting a Putative Manifold to Noisy Data · COLT 2018
Machine learning › Representation and self-supervised learning › representation learning › dimensionality reduction
manifold learning		 0.312018
Fitting a Putative Manifold to Noisy Data · COLT 2018
Computational geometry › geometric modeling and processing › point cloud analysis › geometric reconstruction
manifold reconstruction		 0.312018
Fitting a Putative Manifold to Noisy Data · COLT 2018
Information theory
noisy observations		 0.312018
Fitting a Putative Manifold to Noisy Data · COLT 2018

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

reach estimation · 0.7hausdorff distance · 0.7
YearPublicationVenuePosition
2018 Fitting a Putative Manifold to Noisy Data
abstract
In the present work, we give a solution to the following question from manifold learning. Suppose data belonging to a high dimensional Euclidean space is drawn independently, identically distributed from a measure supported on a low dimensional twice differentiable embedded manifold $M$, and corrupted by a small amount of gaussian noise. How can we produce a manifold $M’$ whose Hausdorff distance to $M$ is small and whose reach is not much smaller than the reach of $M$?
Charles Fefferman, Sergei Ivanov 0001, Yaroslav Kurylev, Matti Lassas, Hariharan Narayanan 0001
 COLT3