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Jan Erik Swiadek

dblp:343/0691 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0001-7936-4795ORCID · verified

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

Artificial intelligence and machine learning · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021

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.

Theoretical computer science
1 paper
Approximation and online algorithms · 67% Computational geometry · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Approximation and online algorithms
approximation algorithms
1.012026
A Constant-Factor Approximation for Continuous Dynamic Time Warping in 2D · ICALP 2026
Approximation and online algorithms › approximation algorithms
constant-factor approximation
1.012026
A Constant-Factor Approximation for Continuous Dynamic Time Warping in 2D · ICALP 2026
Computational geometry › curve similarity
fréchet distance
1.012026
A Constant-Factor Approximation for Continuous Dynamic Time Warping in 2D · ICALP 2026

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

approximation algorithm · 1.0
YearPublicationVenuePosition
2026 A Constant-Factor Approximation for Continuous Dynamic Time Warping in 2D
abstract
Continuous Dynamic Time Warping (CDTW) is a robust similarity measure for polygonal curves that has recently found a variety of applications. Despite its practical use, not much is known about the algorithmic complexity of computing it in 2D, especially when one requires either an exact solution or strong approximation guarantees. We fill this gap by introducing a 5-approximation algorithm with running time O(n⁵) under the 1-norm. This is the first constant-factor approximation for 2D CDTW with polynomial running time. We extend our algorithm to all polygonal norms on ℝ², which we subsequently use in order to achieve a (5+ε)-approximation with time complexity O(n⁵/ε^{1/2}) for CDTW in 2D under any fixed norm. The latter result in particular includes the usual Euclidean 2-norm.
Kevin Buchin, Maike Buchin, Jan Erik Swiadek, Sampson Wong
ICALP3
2022 ADEPT: Anomaly Detection, Explanation and Processing for Time Series with a Focus on Energy Consumption Data
Benedikt Tobias Müller, Marvin Ender, Jan Erik Swiadek, Mengcheng Jin, Simon Winkel, Dominik Niedziela, Bin Li 0089, Jelle Hüntelmann, Emmanuel Müller
ECML/PKDD (6)3