6 Search Results for "Silvestri, Francesco"


Document
Enumerating Subgraphs of Constant Sizes in External Memory

Authors: Shiyuan Deng, Francesco Silvestri, and Yufei Tao

Published in: LIPIcs, Volume 255, 26th International Conference on Database Theory (ICDT 2023)


Abstract
We present an indivisible I/O-efficient algorithm for subgraph enumeration, where the objective is to list all the subgraphs of a massive graph G : = (V, E) that are isomorphic to a pattern graph Q having k = O(1) vertices. Our algorithm performs O((|E|^{k/2})/(M^{{k/2}-1} B) log_{M/B}(|E|/B) + (|E|^ρ)/(M^{ρ-1} B) I/Os with high probability, where ρ is the fractional edge covering number of Q (it always holds ρ ≥ k/2, regardless of Q), M is the number of words in (internal) memory, and B is the number of words in a disk block. Our solution is optimal in the class of indivisible algorithms for all pattern graphs with ρ > k/2. When ρ = k/2, our algorithm is still optimal as long as M/B ≥ (|E|/B)^ε for any constant ε > 0.

Cite as

Shiyuan Deng, Francesco Silvestri, and Yufei Tao. Enumerating Subgraphs of Constant Sizes in External Memory. In 26th International Conference on Database Theory (ICDT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 255, pp. 4:1-4:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{deng_et_al:LIPIcs.ICDT.2023.4,
  author =	{Deng, Shiyuan and Silvestri, Francesco and Tao, Yufei},
  title =	{{Enumerating Subgraphs of Constant Sizes in External Memory}},
  booktitle =	{26th International Conference on Database Theory (ICDT 2023)},
  pages =	{4:1--4:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-270-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{255},
  editor =	{Geerts, Floris and Vandevoort, Brecht},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2023.4},
  URN =		{urn:nbn:de:0030-drops-177460},
  doi =		{10.4230/LIPIcs.ICDT.2023.4},
  annote =	{Keywords: Subgraph Enumeration, Conjunctive Queries, External Memory, Algorithms}
}
Document
On the Bike Spreading Problem

Authors: Elia Costa and Francesco Silvestri

Published in: OASIcs, Volume 96, 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)


Abstract
A free-floating bike-sharing system (FFBSS) is a dockless rental system where an individual can borrow a bike and returns it anywhere, within the service area. To improve the rental service, available bikes should be distributed over the entire service area: a customer leaving from any position is then more likely to find a near bike and then to use the service. Moreover, spreading bikes among the entire service area increases urban spatial equity since the benefits of FFBSS are not a prerogative of just a few zones. For guaranteeing such distribution, the FFBSS operator can use vans to manually relocate bikes, but it incurs high economic and environmental costs. We propose a novel approach that exploits the existing bike flows generated by customers to distribute bikes. More specifically, by envisioning the problem as an Influence Maximization problem, we show that it is possible to position batches of bikes on a small number of zones, and then the daily use of FFBSS will efficiently spread these bikes on a large area. We show that detecting these zones is NP-complete, but there exists a simple and efficient 1-1/e approximation algorithm; our approach is then evaluated on a dataset of rides from the free-floating bike-sharing system of the city of Padova.

Cite as

Elia Costa and Francesco Silvestri. On the Bike Spreading Problem. In 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021). Open Access Series in Informatics (OASIcs), Volume 96, pp. 5:1-5:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{costa_et_al:OASIcs.ATMOS.2021.5,
  author =	{Costa, Elia and Silvestri, Francesco},
  title =	{{On the Bike Spreading Problem}},
  booktitle =	{21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)},
  pages =	{5:1--5:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-213-6},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{96},
  editor =	{M\"{u}ller-Hannemann, Matthias and Perea, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2021.5},
  URN =		{urn:nbn:de:0030-drops-148746},
  doi =		{10.4230/OASIcs.ATMOS.2021.5},
  annote =	{Keywords: Mobility data, bike sharing, bike relocation, influence maximization, NP-completeness, approximation algorithm}
}
Document
Approximate Similarity Search Under Edit Distance Using Locality-Sensitive Hashing

Authors: Samuel McCauley

Published in: LIPIcs, Volume 186, 24th International Conference on Database Theory (ICDT 2021)


Abstract
Edit distance similarity search, also called approximate pattern matching, is a fundamental problem with widespread database applications. The goal of the problem is to preprocess n strings of length d, to quickly answer queries q of the form: if there is a database string within edit distance r of q, return a database string within edit distance cr of q. Previous approaches to this problem either rely on very large (superconstant) approximation ratios c, or very small search radii r. Outside of a narrow parameter range, these solutions are not competitive with trivially searching through all n strings. In this work we give a simple and easy-to-implement hash function that can quickly answer queries for a wide range of parameters. Specifically, our strategy can answer queries in time Õ(d3^rn^{1/c}). The best known practical results require c ≫ r to achieve any correctness guarantee; meanwhile, the best known theoretical results are very involved and difficult to implement, and require query time that can be loosely bounded below by 24^r. Our results significantly broaden the range of parameters for which there exist nontrivial theoretical bounds, while retaining the practicality of a locality-sensitive hash function.

Cite as

Samuel McCauley. Approximate Similarity Search Under Edit Distance Using Locality-Sensitive Hashing. In 24th International Conference on Database Theory (ICDT 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 186, pp. 21:1-21:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{mccauley:LIPIcs.ICDT.2021.21,
  author =	{McCauley, Samuel},
  title =	{{Approximate Similarity Search Under Edit Distance Using Locality-Sensitive Hashing}},
  booktitle =	{24th International Conference on Database Theory (ICDT 2021)},
  pages =	{21:1--21:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-179-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{186},
  editor =	{Yi, Ke and Wei, Zhewei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2021.21},
  URN =		{urn:nbn:de:0030-drops-137299},
  doi =		{10.4230/LIPIcs.ICDT.2021.21},
  annote =	{Keywords: edit distance, approximate pattern matching, approximate nearest neighbor, similarity search, locality-sensitive hashing}
}
Document
Locality-Sensitive Hashing of Curves

Authors: Anne Driemel and Francesco Silvestri

Published in: LIPIcs, Volume 77, 33rd International Symposium on Computational Geometry (SoCG 2017)


Abstract
We study data structures for storing a set of polygonal curves in R^d such that, given a query curve, we can efficiently retrieve similar curves from the set, where similarity is measured using the discrete Fréchet distance or the dynamic time warping distance. To this end we devise the first locality-sensitive hashing schemes for these distance measures. A major challenge is posed by the fact that these distance measures internally optimize the alignment between the curves. We give solutions for different types of alignments including constrained and unconstrained versions. For unconstrained alignments, we improve over a result by Indyk [SoCG 2002] for short curves. Let n be the number of input curves and let m be the maximum complexity of a curve in the input. In the particular case where m <= (a/(4d)) log n, for some fixed a>0, our solutions imply an approximate near-neighbor data structure for the discrete Fréchet distance that uses space in O(n^(1+a) log n) and achieves query time in O(n^a log^2 n) and constant approximation factor. Furthermore, our solutions provide a trade-off between approximation quality and computational performance: for any parameter k in [m], we can give a data structure that uses space in O(2^(2k) m^(k-1) n log n + nm), answers queries in O( 2^(2k) m^(k) log n) time and achieves approximation factor in O(m/k).

Cite as

Anne Driemel and Francesco Silvestri. Locality-Sensitive Hashing of Curves. In 33rd International Symposium on Computational Geometry (SoCG 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 77, pp. 37:1-37:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@InProceedings{driemel_et_al:LIPIcs.SoCG.2017.37,
  author =	{Driemel, Anne and Silvestri, Francesco},
  title =	{{Locality-Sensitive Hashing of Curves}},
  booktitle =	{33rd International Symposium on Computational Geometry (SoCG 2017)},
  pages =	{37:1--37:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-038-5},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{77},
  editor =	{Aronov, Boris and Katz, Matthew J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2017.37},
  URN =		{urn:nbn:de:0030-drops-72032},
  doi =		{10.4230/LIPIcs.SoCG.2017.37},
  annote =	{Keywords: Locality-Sensitive Hashing, Frechet distance, Dynamic Time Warping}
}
Document
Communication Lower Bounds for Distributed-Memory Computations

Authors: Michele Scquizzato and Francesco Silvestri

Published in: LIPIcs, Volume 25, 31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014)


Abstract
In this paper we propose a new approach to the study of the communication requirements of distributed computations, which advocates for the removal of the restrictive assumptions under which earlier results were derived. We illustrate our approach by giving tight lower bounds on the communication complexity required to solve several computational problems in a distributed-memory parallel machine, namely standard matrix multiplication, stencil computations, comparison sorting, and the Fast Fourier Transform. Our bounds rely only on a mild assumption on work distribution, and significantly strengthen previous results which require either the computation to be balanced among the processors, or specific initial distributions of the input data, or an upper bound on the size of processors' local memories.

Cite as

Michele Scquizzato and Francesco Silvestri. Communication Lower Bounds for Distributed-Memory Computations. In 31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014). Leibniz International Proceedings in Informatics (LIPIcs), Volume 25, pp. 627-638, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{scquizzato_et_al:LIPIcs.STACS.2014.627,
  author =	{Scquizzato, Michele and Silvestri, Francesco},
  title =	{{Communication Lower Bounds for Distributed-Memory Computations}},
  booktitle =	{31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014)},
  pages =	{627--638},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-65-1},
  ISSN =	{1868-8969},
  year =	{2014},
  volume =	{25},
  editor =	{Mayr, Ernst W. and Portier, Natacha},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2014.627},
  URN =		{urn:nbn:de:0030-drops-44937},
  doi =		{10.4230/LIPIcs.STACS.2014.627},
  annote =	{Keywords: Communication, lower bounds, distributed memory, parallel algorithms, BSP}
}
Document
Dynamic programming in faulty memory hierarchies (cache-obliviously)

Authors: Saverio Caminiti, Irene Finocchi, Emanuele G. Fusco, and Francesco Silvestri

Published in: LIPIcs, Volume 13, IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2011)


Abstract
Random access memories suffer from transient errors that lead the logical state of some bits to be read differently from how they were last written. Due to technological constraints, caches in the memory hierarchy of modern computer platforms appear to be particularly prone to bit flips. Since algorithms implicitly assume data to be stored in reliable memories, they might easily exhibit unpredictable behaviors even in the presence of a small number of faults. In this paper we investigate the design of dynamic programming algorithms in faulty memory hierarchies. Previous works on resilient algorithms considered a one-level faulty memory model and, with respect to dynamic programming, could address only problems with local dependencies. Our improvement upon these works is two-fold: (1) we significantly extend the class of problems that can be solved resiliently via dynamic programming in the presence of faults, settling challenging non-local problems such as all-pairs shortest paths and matrix multiplication; (2) we investigate the connection between resiliency and cache-efficiency, providing cache-oblivious implementations that incur an (almost) optimal number of cache misses. Our approach yields the first resilient algorithms that can tolerate faults at any level of the memory hierarchy, while maintaining cache-efficiency. All our algorithms are correct with high probability and match the running time and cache misses of their standard non-resilient counterparts while tolerating a large (polynomial) number of faults. Our results also extend to Fast Fourier Transform.

Cite as

Saverio Caminiti, Irene Finocchi, Emanuele G. Fusco, and Francesco Silvestri. Dynamic programming in faulty memory hierarchies (cache-obliviously). In IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2011). Leibniz International Proceedings in Informatics (LIPIcs), Volume 13, pp. 433-444, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


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@InProceedings{caminiti_et_al:LIPIcs.FSTTCS.2011.433,
  author =	{Caminiti, Saverio and Finocchi, Irene and Fusco, Emanuele G. and Silvestri, Francesco},
  title =	{{Dynamic programming in faulty memory hierarchies (cache-obliviously)}},
  booktitle =	{IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2011)},
  pages =	{433--444},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-34-7},
  ISSN =	{1868-8969},
  year =	{2011},
  volume =	{13},
  editor =	{Chakraborty, Supratik and Kumar, Amit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2011.433},
  URN =		{urn:nbn:de:0030-drops-33241},
  doi =		{10.4230/LIPIcs.FSTTCS.2011.433},
  annote =	{Keywords: Unreliable memories, fault-tolerant algorithms, dynamic programming, cache-oblivious algorithms, Gaussian elimination paradigm}
}
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