4 Search Results for "Afshar, Ramtin"


Document
Noisy Sorting Without Searching: Data Oblivious Sorting with Comparison Errors

Authors: Ramtin Afshar, Michael Dillencourt, Michael T. Goodrich, and Evrim Ozel

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)


Abstract
We provide and study several algorithms for sorting an array of n comparable distinct elements subject to probabilistic comparison errors. In this model, the comparison of two elements returns the wrong answer according to a fixed probability, p_e < 1/2, and otherwise returns the correct answer. The dislocation of an element is the distance between its position in a given (current or output) array and its position in a sorted array. There are various algorithms that can be utilized for sorting or near-sorting elements subject to probabilistic comparison errors, but these algorithms are not data oblivious because they all make heavy use of noisy binary searching. In this paper, we provide new methods for sorting with comparison errors that are data oblivious while avoiding the use of noisy binary search methods. In addition, we experimentally compare our algorithms and other sorting algorithms.

Cite as

Ramtin Afshar, Michael Dillencourt, Michael T. Goodrich, and Evrim Ozel. Noisy Sorting Without Searching: Data Oblivious Sorting with Comparison Errors. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 8:1-8:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)


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@InProceedings{afshar_et_al:LIPIcs.SEA.2023.8,
  author =	{Afshar, Ramtin and Dillencourt, Michael and Goodrich, Michael T. and Ozel, Evrim},
  title =	{{Noisy Sorting Without Searching: Data Oblivious Sorting with Comparison Errors}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{8:1--8:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.8},
  URN =		{urn:nbn:de:0030-drops-183585},
  doi =		{10.4230/LIPIcs.SEA.2023.8},
  annote =	{Keywords: sorting, algorithms, randomization, experimentation}
}
Document
Efficient Exact Learning Algorithms for Road Networks and Other Graphs with Bounded Clustering Degrees

Authors: Ramtin Afshar, Michael T. Goodrich, and Evrim Ozel

Published in: LIPIcs, Volume 233, 20th International Symposium on Experimental Algorithms (SEA 2022)


Abstract
The completeness of road network data is significant in the quality of various routing services and applications. We introduce an efficient randomized algorithm for exact learning of road networks using simple distance queries, which can find missing roads and improve the quality of routing services. The efficiency of our algorithm depends on a cluster degree parameter, d_max, which is an upper bound on the degrees of vertex clusters defined during our algorithm. Unfortunately, we leave open the problem of theoretically bounding d_max, although we conjecture that d_max is small for road networks and other similar types of graphs. We support this conjecture by experimentally evaluating our algorithm on road network data for the U.S. and 5 European countries of various sizes. This analysis provides experimental evidence that our algorithm issues a quasilinear number of queries in expectation for road networks and similar graphs.

Cite as

Ramtin Afshar, Michael T. Goodrich, and Evrim Ozel. Efficient Exact Learning Algorithms for Road Networks and Other Graphs with Bounded Clustering Degrees. In 20th International Symposium on Experimental Algorithms (SEA 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 233, pp. 9:1-9:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)


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@InProceedings{afshar_et_al:LIPIcs.SEA.2022.9,
  author =	{Afshar, Ramtin and Goodrich, Michael T. and Ozel, Evrim},
  title =	{{Efficient Exact Learning Algorithms for Road Networks and Other Graphs with Bounded Clustering Degrees}},
  booktitle =	{20th International Symposium on Experimental Algorithms (SEA 2022)},
  pages =	{9:1--9:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-251-8},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{233},
  editor =	{Schulz, Christian and U\c{c}ar, Bora},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2022.9},
  URN =		{urn:nbn:de:0030-drops-165432},
  doi =		{10.4230/LIPIcs.SEA.2022.9},
  annote =	{Keywords: Road Networks, Exact Learning, Graph Reconstruction, Randomized Algorithms}
}
Document
Mapping Networks via Parallel kth-Hop Traceroute Queries

Authors: Ramtin Afshar, Michael T. Goodrich, Pedro Matias, and Martha C. Osegueda

Published in: LIPIcs, Volume 219, 39th International Symposium on Theoretical Aspects of Computer Science (STACS 2022)


Abstract
For a source node, v, and target node, w, the traceroute command iteratively issues "kth-hop" queries, for k = 1, 2, … , δ(v,w), which return the name of the kth vertex on a shortest path from v to w, where δ(v,w) is the distance between v and w, that is, the number of edges in a shortest-path from v to w. The traceroute command is often used for network mapping applications, the study of the connectivity of networks, and it has been studied theoretically with respect to biases it introduces for network mapping when only a subset of nodes in the network can be the source of traceroute queries. In this paper, we provide efficient network mapping algorithms, that are based on kth-hop traceroute queries. Our results include an algorithm that runs in a constant number of parallel rounds with a subquadratic number of queries under reasonable assumptions about the sampling coverage of the nodes that may issue kth-hop traceroute queries. In addition, we introduce a number of new algorithmic techniques, including a high-probability parametric parallelization of a graph clustering technique of Thorup and Zwick, which may be of independent interest.

Cite as

Ramtin Afshar, Michael T. Goodrich, Pedro Matias, and Martha C. Osegueda. Mapping Networks via Parallel kth-Hop Traceroute Queries. In 39th International Symposium on Theoretical Aspects of Computer Science (STACS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 219, pp. 4:1-4:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)


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@InProceedings{afshar_et_al:LIPIcs.STACS.2022.4,
  author =	{Afshar, Ramtin and Goodrich, Michael T. and Matias, Pedro and Osegueda, Martha C.},
  title =	{{Mapping Networks via Parallel kth-Hop Traceroute Queries}},
  booktitle =	{39th International Symposium on Theoretical Aspects of Computer Science (STACS 2022)},
  pages =	{4:1--4:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-222-8},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{219},
  editor =	{Berenbrink, Petra and Monmege, Benjamin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2022.4},
  URN =		{urn:nbn:de:0030-drops-158142},
  doi =		{10.4230/LIPIcs.STACS.2022.4},
  annote =	{Keywords: Network mapping, graph algorithms, parallel algorithms, distributed computing, query complexity, kth-hop queries}
}
Document
Reconstructing Biological and Digital Phylogenetic Trees in Parallel

Authors: Ramtin Afshar, Michael T. Goodrich, Pedro Matias, and Martha C. Osegueda

Published in: LIPIcs, Volume 173, 28th Annual European Symposium on Algorithms (ESA 2020)


Abstract
In this paper, we study the parallel query complexity of reconstructing biological and digital phylogenetic trees from simple queries involving their nodes. This is motivated from computational biology, data protection, and computer security settings, which can be abstracted in terms of two parties, a responder, Alice, who must correctly answer queries of a given type regarding a degree-d tree, T, and a querier, Bob, who issues batches of queries, with each query in a batch being independent of the others, so as to eventually infer the structure of T. We show that a querier can efficiently reconstruct an n-node degree-d tree, T, with a logarithmic number of rounds and quasilinear number of queries, with high probability, for various types of queries, including relative-distance queries and path queries. Our results are all asymptotically optimal and improve the asymptotic (sequential) query complexity for one of the problems we study. Moreover, through an experimental analysis using both real-world and synthetic data, we provide empirical evidence that our algorithms provide significant parallel speedups while also improving the total query complexities for the problems we study.

Cite as

Ramtin Afshar, Michael T. Goodrich, Pedro Matias, and Martha C. Osegueda. Reconstructing Biological and Digital Phylogenetic Trees in Parallel. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 3:1-3:24, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)


Copy BibTex To Clipboard

@InProceedings{afshar_et_al:LIPIcs.ESA.2020.3,
  author =	{Afshar, Ramtin and Goodrich, Michael T. and Matias, Pedro and Osegueda, Martha C.},
  title =	{{Reconstructing Biological and Digital Phylogenetic Trees in Parallel}},
  booktitle =	{28th Annual European Symposium on Algorithms (ESA 2020)},
  pages =	{3:1--3:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-162-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{173},
  editor =	{Grandoni, Fabrizio and Herman, Grzegorz and Sanders, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2020.3},
  URN =		{urn:nbn:de:0030-drops-128696},
  doi =		{10.4230/LIPIcs.ESA.2020.3},
  annote =	{Keywords: Tree Reconstruction, Parallel Algorithms, Privacy, Phylogenetic Trees, Data Structures, Hierarchical Clustering}
}
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