187 Search Results for "Sanders, Peter"

Volume

LIPIcs, Volume 173

28th Annual European Symposium on Algorithms (ESA 2020)

ESA 2020, September 7-9, 2020, Pisa, Italy (Virtual Conference)

Editors: Fabrizio Grandoni, Grzegorz Herman, and Peter Sanders

Artifact
Software
DOI: 10.4230/artifacts.24666
KaMinPar

Authors: Lars Gottesbüren, Nikolai Maas, Dominik Rosch, Peter Sanders, and Daniel Seemaier

Abstract
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Lars Gottesbüren, Nikolai Maas, Dominik Rosch, Peter Sanders, Daniel Seemaier. KaMinPar (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{dagstuhl-artifact-24666,
   title = {{KaMinPar}}, 
   author = {Gottesb\"{u}ren, Lars and Maas, Nikolai and Rosch, Dominik and Sanders, Peter and Seemaier, Daniel},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:2ec38dbccb676136f71dc1796d6a06b450c48c6d}{\texttt{swh:1:dir:2ec38dbccb676136f71dc1796d6a06b450c48c6d}} (visited on 2025-10-01)},
   url = {https://github.com/KaHIP/KaMinPar/commit/73eeaa2371c6826e166c9ca1383996f14d8c7a2a},
   doi = {10.4230/artifacts.24666},
}
Artifact
Software
DOI: 10.4230/artifacts.24698
Engineering Minimal k-Perfect Hash Functions

Authors: Stefan Hermann, Sebastian Kirmayer, Hans-Peter Lehmann, and Stefan Walzer

Abstract
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Stefan Hermann, Sebastian Kirmayer, Hans-Peter Lehmann, Stefan Walzer. Engineering Minimal k-Perfect Hash Functions (Software). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{sourceCodekPHF,
   title = {{Engineering Minimal k-Perfect Hash Functions}}, 
   author = {Hermann, Stefan and Kirmayer, Sebastian and Lehmann, Hans-Peter and Walzer, Stefan},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:e6756f018691a80adc68d839fd3617d8f5e2d0b0;origin=https://github.com/stefanfred/engineering-k-perfect-hashing;visit=swh:1:snp:8b568d1c8fe1e13f6ef95d3b2774fc59c259d6b5;anchor=swh:1:rev:2c269037dad34b69a68b56fed38c98656f02c133}{\texttt{swh:1:dir:e6756f018691a80adc68d839fd3617d8f5e2d0b0}} (visited on 2025-10-01)},
   url = {https://github.com/stefanfred/engineering-k-perfect-hashing},
   doi = {10.4230/artifacts.24698},
}
Artifact
Software
DOI: 10.4230/artifacts.23789
ByteHamster/ConsensusRecSplit

Authors: Hans-Peter Lehmann, Peter Sanders, Stefan Walzer, and Jonatan Ziegler

Abstract
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Hans-Peter Lehmann, Peter Sanders, Stefan Walzer, Jonatan Ziegler. ByteHamster/ConsensusRecSplit (Software, Source code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{dagstuhl-artifact-23789,
   title = {{ByteHamster/ConsensusRecSplit}}, 
   author = {Lehmann, Hans-Peter and Sanders, Peter and Walzer, Stefan and Ziegler, Jonatan},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:eeef738e12bea287eae54a77ce81241587a91767;origin=https://github.com/ByteHamster/ConsensusRecSplit;visit=swh:1:snp:4e488d15839a07248b34bebacd139581927693ba;anchor=swh:1:rev:11deea62b5b507fbac5419ad14c9e2cc0b3ffff8}{\texttt{swh:1:dir:eeef738e12bea287eae54a77ce81241587a91767}} (visited on 2025-10-01)},
   url = {https://github.com/ByteHamster/ConsensusRecSplit},
   doi = {10.4230/artifacts.23789},
}
Artifact
Software
DOI: 10.4230/artifacts.23790
ByteHamster/MPHF-Experiments

Authors: Hans-Peter Lehmann

Abstract
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Hans-Peter Lehmann. ByteHamster/MPHF-Experiments (Software, Comparison with competitors). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{dagstuhl-artifact-23790,
   title = {{ByteHamster/MPHF-Experiments}}, 
   author = {Lehmann, Hans-Peter},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:7b02eda8ffa5a9d61a086ff2fc34fb0fbdc3eff4;origin=https://github.com/ByteHamster/MPHF-Experiments;visit=swh:1:snp:368a276aa02ccd3cf9f73f14764499ba9a4bff85;anchor=swh:1:rev:d4501ce780b534f0c5a285874558788e49ff3198}{\texttt{swh:1:dir:7b02eda8ffa5a9d61a086ff2fc34fb0fbdc3eff4}} (visited on 2025-10-01)},
   url = {https://github.com/ByteHamster/MPHF-Experiments},
   doi = {10.4230/artifacts.23790},
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.3
Generalized Graph Packing Problems Parameterized by Treewidth

Authors: Barış Can Esmer and Dániel Marx

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
H-Packing is the problem of finding a maximum number of vertex-disjoint copies of H in a given graph G. H-Partition is the special case of finding a set of vertex-disjoint copies that cover each vertex of G exactly once. Our goal is to study these problems and some generalizations on bounded-treewidth graphs. The case of H being a triangle is well understood: given a tree decomposition of G having treewidth tw, the K₃-Packing problem can be solved in time 2^tw⋅ n^O(1), while Lokshtanov et al. [ACM Transactions on Algorithms 2018] showed, under the Strong Exponential-Time Hypothesis (SETH), that there is no (2-ε)^tw⋅ n^O(1) algorithm for any ε > 0 even for K₃-Partition. Similar results can be obtained for any other clique K_d for d ≥ 3. We provide generalizations in two directions: - We consider a generalization of the problem where every vertex can be used at most c times for some c ≥ 1. When H is any clique K_d with d ≥ 3, then we give upper and lower bounds showing that the optimal running time increases to (c+1)^tw⋅ n^O(1). We consider two variants depending on whether a copy of H can be used multiple times in the packing. - If H is not a clique, then the dependence of the running time on treewidth may not be even single exponential. Specifically, we show that if H is any fixed graph where not every 2-connected component is a clique, then there is no 2^o(tw log tw)⋅ n^O(1) algorithm for H-Partition, assuming the Exponential-Time Hypothesis (ETH).
Cite as

Barış Can Esmer and Dániel Marx. Generalized Graph Packing Problems Parameterized by Treewidth. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{canesmer_et_al:LIPIcs.ESA.2025.3,
  author =	{Can Esmer, Bar{\i}\c{s} and Marx, D\'{a}niel},
  title =	{{Generalized Graph Packing Problems Parameterized by Treewidth}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{3:1--3:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.3},
  URN =		{urn:nbn:de:0030-drops-244713},
  doi =		{10.4230/LIPIcs.ESA.2025.3},
  annote =	{Keywords: Graph Packing, Graph Partitioning, Parameterized Complexity, Treewidth, Pathwidth, pw-SETH, Single-Exponential Lower Bound, Slightly Superexponential Lower Bound}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.47
Fast and Lightweight Distributed Suffix Array Construction

Authors: Manuel Haag, Florian Kurpicz, Peter Sanders, and Matthias Schimek

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
The suffix array contains the lexicographical order of all suffixes of a text. It is one of the most well-studied text indices with applications in bioinformatics, compression, and pattern matching. The main bottleneck of distributed-memory suffix array construction algorithms is their memory requirements. Even careful implementations require 30×-60× the input size as working memory. We present a scalable and lightweight distributed-memory adaptation of the difference cover (DCX) suffix array construction algorithm. Our approach relies on novel bucketing and random chunk redistribution techniques which reduce our memory requirement to 20×-26× the input size for medium-sized inputs and to 14×-15× for large-sized inputs. Regarding running time, we achieve speedups of up to 5× over current state-of-the-art distributed suffix array construction algorithms.
Cite as

Manuel Haag, Florian Kurpicz, Peter Sanders, and Matthias Schimek. Fast and Lightweight Distributed Suffix Array Construction. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 47:1-47:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{haag_et_al:LIPIcs.ESA.2025.47,
  author =	{Haag, Manuel and Kurpicz, Florian and Sanders, Peter and Schimek, Matthias},
  title =	{{Fast and Lightweight Distributed Suffix Array Construction}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{47:1--47:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.47},
  URN =		{urn:nbn:de:0030-drops-245154},
  doi =		{10.4230/LIPIcs.ESA.2025.47},
  annote =	{Keywords: Distributed Computing, Suffix Array Construction}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.32
Linear-Time Multilevel Graph Partitioning via Edge Sparsification

Authors: Lars Gottesbüren, Nikolai Maas, Dominik Rosch, Peter Sanders, and Daniel Seemaier

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
The current landscape of balanced graph partitioning is divided into high-quality but expensive multilevel algorithms and cheaper approaches with linear running time, such as single-level algorithms and streaming algorithms. We demonstrate how to achieve the best of both worlds with a linear time multilevel algorithm. Multilevel algorithms construct a hierarchy of increasingly smaller graphs by repeatedly contracting clusters of nodes. Our approach preserves their distinct advantage, allowing refinement of the partition over multiple levels with increasing detail. At the same time, we use edge sparsification to guarantee geometric size reduction between the levels and thus linear running time. We provide a proof of the linear running time as well as additional insights into the behavior of multilevel algorithms, showing that graphs with low modularity are most likely to trigger worst-case running time. We evaluate multiple approaches for edge sparsification and integrate our algorithm into the state-of-the-art multilevel partitioner KaMinPar, maintaining its excellent parallel scalability. As demonstrated in detailed experiments, this results in a 1.49× average speedup (up to 4× for some instances) with only 1% loss in solution quality. Moreover, our algorithm clearly outperforms state-of-the-art single-level and streaming approaches.
Cite as

Lars Gottesbüren, Nikolai Maas, Dominik Rosch, Peter Sanders, and Daniel Seemaier. Linear-Time Multilevel Graph Partitioning via Edge Sparsification. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 32:1-32:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gottesburen_et_al:LIPIcs.ESA.2025.32,
  author =	{Gottesb\"{u}ren, Lars and Maas, Nikolai and Rosch, Dominik and Sanders, Peter and Seemaier, Daniel},
  title =	{{Linear-Time Multilevel Graph Partitioning via Edge Sparsification}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{32:1--32:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.32},
  URN =		{urn:nbn:de:0030-drops-245007},
  doi =		{10.4230/LIPIcs.ESA.2025.32},
  annote =	{Keywords: Graph Partitioning, Graph Algorithms, Linear Time Algorithms, Graph Sparsification}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.30
Reconstructing Random Graphs from Distance Queries

Authors: Michael Krivelevich and Maksim Zhukovskii

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
We estimate the minimum number of distance queries that is sufficient to reconstruct the binomial random graph G(n,p) with constant diameter with high probability. We get a tight (up to a constant factor) answer for all p > n^{-1+o(1)} outside "threshold windows" around n^{-k/(k+1)+o(1)}, k ∈ ℤ_{> 0}: with high probability the query complexity equals Θ(n^{4-d}p^{2-d}), where d is the diameter of the random graph. This demonstrates the following non-monotone behaviour: the query complexity jumps down at moments when the diameter gets larger; yet, between these moments the query complexity grows. We also show that there exists a non-adaptive algorithm that reconstructs the random graph with O(n^{4-d}p^{2-d}ln n) distance queries with high probability, and this is best possible.
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Michael Krivelevich and Maksim Zhukovskii. Reconstructing Random Graphs from Distance Queries. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 30:1-30:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{krivelevich_et_al:LIPIcs.ESA.2025.30,
  author =	{Krivelevich, Michael and Zhukovskii, Maksim},
  title =	{{Reconstructing Random Graphs from Distance Queries}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{30:1--30:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.30},
  URN =		{urn:nbn:de:0030-drops-244982},
  doi =		{10.4230/LIPIcs.ESA.2025.30},
  annote =	{Keywords: random graphs, graph reconstruction, distance queries, query complexity}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.27
Online Makespan Scheduling Under Scenarios

Authors: Ekin Ergen

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
We consider a natural extension of online makespan scheduling on identical parallel machines by introducing scenarios. A scenario is a subset of jobs, and the task of our problem is to find a global assignment of the jobs to machines so that the maximum makespan under a scenario, i.e., the maximum makespan of any schedule restricted to a scenario, is minimized. For varying values of the number of scenarios and machines, we explore the competitiveness of online algorithms. We prove tight and near-tight bounds, several of which are achieved through novel constructions. In particular, we leverage the interplay between the unit processing time case of our problem and the hypergraph coloring problem both ways: We use hypergraph coloring techniques to steer an adversarial family of instances proving lower bounds for our problem, which in turn leads to lower bounds for several variants of online hypergraph coloring.
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Ekin Ergen. Online Makespan Scheduling Under Scenarios. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 27:1-27:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ergen:LIPIcs.ESA.2025.27,
  author =	{Ergen, Ekin},
  title =	{{Online Makespan Scheduling Under Scenarios}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{27:1--27:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.27},
  URN =		{urn:nbn:de:0030-drops-244950},
  doi =		{10.4230/LIPIcs.ESA.2025.27},
  annote =	{Keywords: online scheduling, scenario-based model, online algorithms}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.79
Semi-Streaming Algorithms for Hypergraph Matching

Authors: Henrik Reinstädtler, S M Ferdous, Alex Pothen, Bora Uçar, and Christian Schulz

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
We propose two one-pass streaming algorithms for the NP-hard hypergraph matching problem. The first algorithm stores a small subset of potential matching edges in a stack using dual variables to select edges. It has an approximation guarantee of 1/(d(1+ε)) and requires 𝒪((n/ε)log²n) bits of memory, where n is the number of vertices in the hypergraph, d is the maximum number of vertices in a hyperedge, and ε > 0 is a parameter to be chosen. The second algorithm computes, stores, and updates a single matching as the edges stream, with an approximation ratio dependent on a parameter α. Its best approximation guarantee is 1/((2d-1) + 2 √{d(d-1)}), and it requires only 𝒪(n) memory. We have implemented both algorithms and compared them with respect to solution quality, memory consumption, and running times on two diverse sets of hypergraphs with a non-streaming greedy and a naive streaming algorithm. Our results show that the streaming algorithms achieve much better solution quality than naive algorithms when facing adverse orderings. Furthermore, these algorithms reduce the memory required by a factor of 13 in the geometric mean on our test problems, and also outperform the offline Greedy algorithm in running time.
Cite as

Henrik Reinstädtler, S M Ferdous, Alex Pothen, Bora Uçar, and Christian Schulz. Semi-Streaming Algorithms for Hypergraph Matching. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 79:1-79:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{reinstadtler_et_al:LIPIcs.ESA.2025.79,
  author =	{Reinst\"{a}dtler, Henrik and Ferdous, S M and Pothen, Alex and U\c{c}ar, Bora and Schulz, Christian},
  title =	{{Semi-Streaming Algorithms for Hypergraph Matching}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{79:1--79:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.79},
  URN =		{urn:nbn:de:0030-drops-245478},
  doi =		{10.4230/LIPIcs.ESA.2025.79},
  annote =	{Keywords: hypergraph, matching, semi-streaming}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.8
Fast Computation of k-Runs, Parameterized Squares, and Other Generalised Squares

Authors: Yuto Nakashima, Jakub Radoszewski, and Tomasz Waleń

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
A k-mismatch square is a string of the form XY where X and Y are two equal-length strings that have at most k mismatches. Kolpakov and Kucherov [Theor. Comput. Sci., 2003] defined two notions of k-mismatch repeats, called k-repetitions and k-runs, each representing a sequence of consecutive k-mismatch squares of equal length. They proposed algorithms for computing k-repetitions and k-runs working in 𝒪(nklog k+output) time for a string of length n over an integer alphabet, where output is the number of the reported repeats. We show that output = 𝒪(nk log k), both in case of k-repetitions and k-runs, which implies that the complexity of their algorithms is actually 𝒪(nk log k). We apply this result to computing parameterized squares. A parameterized square is a string of the form XY such that X and Y parameterized-match, i.e., there exists a bijection f on the alphabet such that f(X) = Y. Two parameterized squares XY and X'Y' are equivalent if they parameterized match. Recently Hamai et al. [SPIRE 2024] showed that a string of length n over an alphabet of size σ contains less than nσ non-equivalent parameterized squares, improving an earlier bound by Kociumaka et al. [Theor. Comput. Sci., 2016]. We apply our bound for k-mismatch repeats to propose an algorithm that reports all non-equivalent parameterized squares in 𝒪(nσ log σ) time. We also show that the number of non-equivalent parameterized squares can be computed in 𝒪(n log n) time. This last algorithm applies to squares under any substring compatible equivalence relation and also to counting squares that are distinct as strings. In particular, this improves upon the 𝒪(nσ)-time algorithm of Gawrychowski et al. [CPM 2023] for counting order-preserving squares that are distinct as strings if σ = ω(log n).
Cite as

Yuto Nakashima, Jakub Radoszewski, and Tomasz Waleń. Fast Computation of k-Runs, Parameterized Squares, and Other Generalised Squares. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 8:1-8:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{nakashima_et_al:LIPIcs.ESA.2025.8,
  author =	{Nakashima, Yuto and Radoszewski, Jakub and Wale\'{n}, Tomasz},
  title =	{{Fast Computation of k-Runs, Parameterized Squares, and Other Generalised Squares}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{8:1--8:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.8},
  URN =		{urn:nbn:de:0030-drops-244768},
  doi =		{10.4230/LIPIcs.ESA.2025.8},
  annote =	{Keywords: string algorithm, k-mismatch square, parameterized square, order-preserving square, maximum gapped repeat}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.18
Efficiency of Learned Indexes on Genome Spectra

Authors: Md. Hasin Abrar, Paul Medvedev, and Giorgio Vinciguerra

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
Data structures on a multiset of genomic k-mers are at the heart of many bioinformatic tools. As genomic datasets grow in scale, the efficiency of these data structures increasingly depends on how well they leverage the inherent patterns in the data. One recent and effective approach is the use of learned indexes that approximate the rank function of a multiset using a piecewise linear function with very few segments. However, theoretical worst-case analysis struggles to predict the practical performance of these indexes. We address this limitation by developing a novel measure of piecewise-linear approximability of the data, called CaPLa (Canonical Piecewise Linear approximability). CaPLa builds on the empirical observation that a power-law model often serves as a reasonable proxy for piecewise linear-approximability, while explicitly accounting for deviations from a true power-law fit. We prove basic properties of CaPLa and present an efficient algorithm to compute it. We then demonstrate that CaPLa can accurately predict space bounds for data structures on real data. Empirically, we analyze over 500 genomes through the lens of CaPLa, revealing that it varies widely across the tree of life and even within individual genomes. Finally, we study the robustness of CaPLa as a measure and the factors that make genomic k-mer multisets different from random ones.
Cite as

Md. Hasin Abrar, Paul Medvedev, and Giorgio Vinciguerra. Efficiency of Learned Indexes on Genome Spectra. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 18:1-18:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{abrar_et_al:LIPIcs.ESA.2025.18,
  author =	{Abrar, Md. Hasin and Medvedev, Paul and Vinciguerra, Giorgio},
  title =	{{Efficiency of Learned Indexes on Genome Spectra}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{18:1--18:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.18},
  URN =		{urn:nbn:de:0030-drops-244865},
  doi =		{10.4230/LIPIcs.ESA.2025.18},
  annote =	{Keywords: Genome spectra, piecewise linear approximation, learned index, k-mers}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.62
Polynomial-Time Constant-Approximation for Fair Sum-Of-Radii Clustering

Authors: Sina Bagheri Nezhad, Sayan Bandyapadhyay, and Tianzhi Chen

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
In a seminal work, Chierichetti et al. [Chierichetti et al., 2017] introduced the (t,k)-fair clustering problem: Given a set of red points and a set of blue points in a metric space, a clustering is called fair if the number of red points in each cluster is at most t times and at least 1/t times the number of blue points in that cluster. The goal is to compute a fair clustering with at most k clusters that optimizes certain objective function. Considering this problem, they designed a polynomial-time O(1)- and O(t)-approximation for the k-center and the k-median objective, respectively. Recently, Carta et al. [Carta et al., 2024] studied this problem with the sum-of-radii objective and obtained a (6+ε)-approximation with running time O((k log_{1+ε}(k/ε))^k n^O(1)), i.e., fixed-parameter tractable in k. Here n is the input size. In this work, we design the first polynomial-time O(1)-approximation for (t,k)-fair clustering with the sum-of-radii objective, improving the result of Carta et al. Our result places sum-of-radii in the same group of objectives as k-center, that admit polynomial-time O(1)-approximations. This result also implies a polynomial-time O(1)-approximation for the Euclidean version of the problem, for which an f(k)⋅n^O(1)-time (1+ε)-approximation was known due to Drexler et al. [Drexler et al., 2023]. Here f is an exponential function of k. We are also able to extend our result to any arbitrary 𝓁 ≥ 2 number of colors when t = 1. This matches known results for the k-center and k-median objectives in this case. The significant disparity of sum-of-radii compared to k-center and k-median presents several complex challenges, all of which we successfully overcome in our work. Our main contribution is a novel cluster-merging-based analysis technique for sum-of-radii that helps us achieve the constant-approximation bounds.
Cite as

Sina Bagheri Nezhad, Sayan Bandyapadhyay, and Tianzhi Chen. Polynomial-Time Constant-Approximation for Fair Sum-Of-Radii Clustering. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 62:1-62:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bagherinezhad_et_al:LIPIcs.ESA.2025.62,
  author =	{Bagheri Nezhad, Sina and Bandyapadhyay, Sayan and Chen, Tianzhi},
  title =	{{Polynomial-Time Constant-Approximation for Fair Sum-Of-Radii Clustering}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{62:1--62:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.62},
  URN =		{urn:nbn:de:0030-drops-245309},
  doi =		{10.4230/LIPIcs.ESA.2025.62},
  annote =	{Keywords: fair clustering, sum-of-radii clustering, approximation algorithms}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.59
Improved Dominance Filtering for Unions and Minkowski Sums of Pareto Sets

Authors: Konstantinos Karathanasis, Spyros Kontogiannis, and Christos Zaroliagis

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
A key task in multi-objective optimization is to compute the Pareto frontier (a.k.a. Pareto subset) P of a given d-dimensional objective space F; that is, a maximal subset P ⊆ F such that every element in P is non-dominated (i.e., it is better in at least one criterion, against any other point) within F. This process, called dominance-filtering, often involves handling objective spaces derived from either the union or the Minkowski sum of two given partial objective spaces which are Pareto sets themselves, and constitutes a major bottleneck in several multi-objective optimization techniques. In this work, we introduce three new data structures, ND^{+}-trees, QND^{+}-trees and TND^{+}-trees, which are designed for efficiently indexing non-dominated objective vectors and performing dominance-checks. We also devise three new algorithms that efficiently filter out dominated objective vectors from the union or the Minkowski sum of two Pareto sets. An extensive experimental evaluation on both synthetically generated and real-world data sets reveals that our new algorithms outperform state-of-art techniques for dominance-filtering of unions and Minkowski sums of Pareto sets, and scale well w.r.t. the number of d ≥ 3 criteria and the sets' sizes.
Cite as

Konstantinos Karathanasis, Spyros Kontogiannis, and Christos Zaroliagis. Improved Dominance Filtering for Unions and Minkowski Sums of Pareto Sets. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 59:1-59:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{karathanasis_et_al:LIPIcs.ESA.2025.59,
  author =	{Karathanasis, Konstantinos and Kontogiannis, Spyros and Zaroliagis, Christos},
  title =	{{Improved Dominance Filtering for Unions and Minkowski Sums of Pareto Sets}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{59:1--59:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.59},
  URN =		{urn:nbn:de:0030-drops-245277},
  doi =		{10.4230/LIPIcs.ESA.2025.59},
  annote =	{Keywords: Multi-Objective Optimization, Multi-Dimensional Data Structures, Pareto Sets, Algorithm Engineering}
}
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