4 Search Results for "Boria, Nicolas"

Document
DOI: 10.4230/LIPIcs.ESA.2024.40
Improved Algorithms for Maximum Coverage in Dynamic and Random Order Streams

Authors: Amit Chakrabarti, Andrew McGregor, and Anthony Wirth

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
The maximum coverage problem is to select k sets, from a collection of m sets, such that the cardinality of their union, in a universe of size n, is maximized. We consider (1-1/e-ε)-approximation algorithms for this NP-hard problem in three standard data stream models. 1) Dynamic Model. The stream consists of a sequence of sets being inserted and deleted. Our multi-pass algorithm uses ε^{-2} k ⋅ polylog(n,m) space. The best previous result (Assadi and Khanna, SODA 2018) used (n +ε^{-4} k) polylog(n,m) space. While both algorithms use O(ε^{-1} log m) passes, our analysis shows that, when ε ≤ 1/log log m, it is possible to reduce the number of passes by a 1/log log m factor without incurring additional space. 2) Random Order Model. In this model, there are no deletions, and the sets forming the instance are uniformly randomly permuted to form the input stream. We show that a single pass and k polylog(n,m) space suffices for arbitrary small constant ε. The best previous result, by Warneke et al. (ESA 2023), used k² polylog(n,m) space. 3) Insert-Only Model. Lastly, our results, along with numerous previous results, use a sub-sampling technique introduced by McGregor and Vu (ICDT 2017) to sparsify the input instance. We explain how this technique and others used in the paper can be implemented such that the amortized update time of our algorithm is polylogarithmic. This also implies an improvement of the state-of-the-art insert only algorithms in terms of the update time: polylog(m,n) update time suffices, whereas the best previous result by Jaud et al. (SEA 2023) required update time that was linear in k.
Cite as

Amit Chakrabarti, Andrew McGregor, and Anthony Wirth. Improved Algorithms for Maximum Coverage in Dynamic and Random Order Streams. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 40:1-40:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{chakrabarti_et_al:LIPIcs.ESA.2024.40,
  author =	{Chakrabarti, Amit and McGregor, Andrew and Wirth, Anthony},
  title =	{{Improved Algorithms for Maximum Coverage in Dynamic and Random Order Streams}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{40:1--40:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John 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.2024.40},
  URN =		{urn:nbn:de:0030-drops-211114},
  doi =		{10.4230/LIPIcs.ESA.2024.40},
  annote =	{Keywords: Data Stream Computation, Maximum Coverage, Submodular Maximization}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2024.25
Maximum Unique Coverage on Streams: Improved FPT Approximation Scheme and Tighter Space Lower Bound

Authors: Philip Cervenjak, Junhao Gan, Seeun William Umboh, and Anthony Wirth

Published in: LIPIcs, Volume 317, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)

Abstract
We consider the Max Unique Coverage problem, including applications to the data stream model. The input is a universe of n elements, a collection of m subsets of this universe, and a cardinality constraint, k. The goal is to select a subcollection of at most k sets that maximizes unique coverage, i.e, the number of elements contained in exactly one of the selected sets. The Max Unique Coverage problem has applications in wireless networks, radio broadcast, and envy-free pricing. Our first main result is a fixed-parameter tractable approximation scheme (FPT-AS) for Max Unique Coverage, parameterized by k and the maximum element frequency, r, which can be implemented on a data stream. Our FPT-AS finds a (1-ε)-approximation while maintaining a kernel of size Õ(k r/ε), which can be combined with subsampling to use Õ(k² r / ε³) space overall. This significantly improves on the previous-best FPT-AS with the same approximation, but a kernel of size Õ(k² r / ε²). In order to achieve our first result, we show upper bounds on the ratio of a collection’s coverage to the unique coverage of a maximizing subcollection; this is by constructing explicit algorithms that find a subcollection with unique coverage at least a logarithmic ratio of the collection’s coverage. We complement our algorithms with our second main result, showing that Ω(m / k²) space is necessary to achieve a (1.5 + o(1))/(ln k - 1)-approximation in the data stream. This dramatically improves the previous-best lower bound showing that Ω(m / k²) is necessary to achieve better than a e^{-1+1/k}-approximation.
Cite as

Philip Cervenjak, Junhao Gan, Seeun William Umboh, and Anthony Wirth. Maximum Unique Coverage on Streams: Improved FPT Approximation Scheme and Tighter Space Lower Bound. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 317, pp. 25:1-25:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{cervenjak_et_al:LIPIcs.APPROX/RANDOM.2024.25,
  author =	{Cervenjak, Philip and Gan, Junhao and Umboh, Seeun William and Wirth, Anthony},
  title =	{{Maximum Unique Coverage on Streams: Improved FPT Approximation Scheme and Tighter Space Lower Bound}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)},
  pages =	{25:1--25:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-348-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{317},
  editor =	{Kumar, Amit and Ron-Zewi, Noga},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2024.25},
  URN =		{urn:nbn:de:0030-drops-210183},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2024.25},
  annote =	{Keywords: Maximum unique coverage, maximum coverage, approximate kernel, data streams}
}
Document
DOI: 10.4230/LIPIcs.WABI.2021.5
The Maximum Duo-Preservation String Mapping Problem with Bounded Alphabet

Authors: Nicolas Boria, Laurent Gourvès, Vangelis Th. Paschos, and Jérôme Monnot

Published in: LIPIcs, Volume 201, 21st International Workshop on Algorithms in Bioinformatics (WABI 2021)

Abstract
Given two strings A and B such that B is a permutation of A, the max duo-preservation string mapping (MPSM) problem asks to find a mapping π between them so as to preserve a maximum number of duos. A duo is any pair of consecutive characters in a string and it is preserved by π if its two consecutive characters in A are mapped to same two consecutive characters in B. This problem has received a growing attention in recent years, partly as an alternative way to produce approximation algorithms for its minimization counterpart, min common string partition, a widely studied problem due its applications in comparative genomics. Considering this favored field of application with short alphabet, it is surprising that MPSM^𝓁, the variant of MPSM with bounded alphabet, has received so little attention, with a single yet impressive work that provides a 2.67-approximation achieved in O(n) [Brubach, 2018], where n = |A| = |B|. Our work focuses on MPSM^𝓁, and our main contribution is the demonstration that this problem admits a Polynomial Time Approximation Scheme (PTAS) when 𝓁 = O(1). We also provide an alternate, somewhat simpler, proof of NP-hardness for this problem compared with the NP-hardness proof presented in [Haitao Jiang et al., 2012].
Cite as

Nicolas Boria, Laurent Gourvès, Vangelis Th. Paschos, and Jérôme Monnot. The Maximum Duo-Preservation String Mapping Problem with Bounded Alphabet. In 21st International Workshop on Algorithms in Bioinformatics (WABI 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 201, pp. 5:1-5:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{boria_et_al:LIPIcs.WABI.2021.5,
  author =	{Boria, Nicolas and Gourv\`{e}s, Laurent and Paschos, Vangelis Th. and Monnot, J\'{e}r\^{o}me},
  title =	{{The Maximum Duo-Preservation String Mapping Problem with Bounded Alphabet}},
  booktitle =	{21st International Workshop on Algorithms in Bioinformatics (WABI 2021)},
  pages =	{5:1--5:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-200-6},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{201},
  editor =	{Carbone, Alessandra and El-Kebir, Mohammed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2021.5},
  URN =		{urn:nbn:de:0030-drops-143586},
  doi =		{10.4230/LIPIcs.WABI.2021.5},
  annote =	{Keywords: Maximum-Duo Preservation String Mapping, Bounded alphabet, Polynomial Time Approximation Scheme}
}
Document
DOI: 10.4230/LIPIcs.CPM.2016.11
A 7/2-Approximation Algorithm for the Maximum Duo-Preservation String Mapping Problem

Authors: Nicolas Boria, Gianpiero Cabodi, Paolo Camurati, Marco Palena, Paolo Pasini, and Stefano Quer

Published in: LIPIcs, Volume 54, 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016)

Abstract
This paper presents a simple 7/2-approximation algorithm for the Maximum Duo-Preservation String Mapping (MPSM) problem. This problem is complementary to the classical and well studied min common string partition problem (MCSP), that computes the minimal edit distance between two strings when the only operation allowed is to shift blocks of characters. The algorithm improves on the previously best-known 4-approximation algorithm by computing a simple local optimum.
Cite as

Nicolas Boria, Gianpiero Cabodi, Paolo Camurati, Marco Palena, Paolo Pasini, and Stefano Quer. A 7/2-Approximation Algorithm for the Maximum Duo-Preservation String Mapping Problem. In 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 54, pp. 11:1-11:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{boria_et_al:LIPIcs.CPM.2016.11,
  author =	{Boria, Nicolas and Cabodi, Gianpiero and Camurati, Paolo and Palena, Marco and Pasini, Paolo and Quer, Stefano},
  title =	{{A 7/2-Approximation Algorithm for the Maximum Duo-Preservation String Mapping Problem}},
  booktitle =	{27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016)},
  pages =	{11:1--11:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-012-5},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{54},
  editor =	{Grossi, Roberto and Lewenstein, Moshe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2016.11},
  URN =		{urn:nbn:de:0030-drops-60875},
  doi =		{10.4230/LIPIcs.CPM.2016.11},
  annote =	{Keywords: Polynomial approximation, Max Duo-Preservation String Mapping Problem, Min Common String Partition Problem, Local Search}
}
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