4 Search Results for "Ramamohanarao, Kotagiri"

Document
DOI: 10.4230/LIPIcs.SEA.2026.1
Global Polyline Simplification Under the Fréchet Distance: Theory and Practice

Authors: Christian Abdullahad and Sabine Storandt

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract
Given an input polyline with n vertices, the global polyline simplification problem seeks a simplified polyline with the minimum number of vertices whose distance to the original polyline does not exceed a given bound. For the vertex-restricted variant, where the simplified polyline is required to be a subsequence of the input vertices, an algorithm with a running time of 𝒪(n³) was presented in previous work, using the Fréchet distance as the polyline similarity measure. A closely related variant is the local polyline simplification problem, in which the distance bound is required to hold for every individual shortcut segment replacing a sub-polyline. This condition implies that any locally valid simplification is also globally valid, whereas the converse does not hold. As a consequence, globally optimal simplifications may use substantially fewer vertices than locally optimal ones. Indeed, in previous work, instances were constructed in which the optimal global simplification is smaller by a constant factor. On the algorithmic side, optimal local simplifications can be computed significantly faster, namely in 𝒪(n² log n) under the Fréchet distance, and efficient heuristics are also available. This raises the question of which problem variant is more suitable for practical application. In this paper, we first show that there exist instances for which the optimal solution sizes of global and local polyline simplification differ by a factor in Θ(n), substantially strengthening the previously known constant-factor separation. We then present the first practical implementations of existing algorithms for global polyline simplification and experimentally evaluate their performance. To this end, we introduce several engineering techniques that considerably accelerate these algorithms. Moreover, we develop an implicit Fréchet framework that allows many Fréchet-related problems to be addressed in a weaker computational model. Within this framework, explicit geometric computations can be reduced to simple comparisons, resulting in significantly more robust implementations. Somewhat surprisingly, our experimental results reveal that, despite the large worst-case gap established by our theoretical result, the difference in solution size between optimal global and local simplifications is negligible in practice. Motivated by this observation, we propose a heuristic for global polyline simplification that is guaranteed to produce solutions of size equal to or smaller than the optimal local simplification. On a benchmark consisting of one million polylines, the heuristic yields suboptimal results on only eight while being significantly faster than the optimal algorithms.
Cite as

Christian Abdullahad and Sabine Storandt. Global Polyline Simplification Under the Fréchet Distance: Theory and Practice. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 1:1-1:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{abdullahad_et_al:LIPIcs.SEA.2026.1,
  author =	{Abdullahad, Christian and Storandt, Sabine},
  title =	{{Global Polyline Simplification Under the Fr\'{e}chet Distance: Theory and Practice}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{1:1--1:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.1},
  URN =		{urn:nbn:de:0030-drops-260055},
  doi =		{10.4230/LIPIcs.SEA.2026.1},
  annote =	{Keywords: Polyline Simplification, Shortcut Graph, Fr\'{e}chet Distance}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2026.5
Rule Rewriting Revisited: A Fresh Look at Static Filtering for Datalog and ASP

Authors: Philipp Hanisch and Markus Krötzsch

Published in: LIPIcs, Volume 365, 29th International Conference on Database Theory (ICDT 2026)

Abstract
Static filtering is a data-independent optimisation method for Datalog, which generalises algebraic query rewriting techniques from relational databases. In spite of its early discovery by Kifer and Lozinskii in 1986, the method has been overlooked in recent research and system development, and special cases are being rediscovered independently. We therefore recall the original approach, using updated terminology and more general filter predicates that capture features of modern systems, and we show how to extend its applicability to answer set programming (ASP). The outcome is strictly more general but also more complex than the classical approach: double exponential in general and single exponential even for predicates of bounded arity. As a solution, we propose tractable approximations of the algorithm that can still yield much improved logic programs in typical cases, e.g., it can improve the performance of rule systems over real-world data in the order of magnitude.
Cite as

Philipp Hanisch and Markus Krötzsch. Rule Rewriting Revisited: A Fresh Look at Static Filtering for Datalog and ASP. In 29th International Conference on Database Theory (ICDT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 365, pp. 5:1-5:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{hanisch_et_al:LIPIcs.ICDT.2026.5,
  author =	{Hanisch, Philipp and Kr\"{o}tzsch, Markus},
  title =	{{Rule Rewriting Revisited: A Fresh Look at Static Filtering for Datalog and ASP}},
  booktitle =	{29th International Conference on Database Theory (ICDT 2026)},
  pages =	{5:1--5:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-413-0},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{365},
  editor =	{ten Cate, Balder and Funk, Maurice},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2026.5},
  URN =		{urn:nbn:de:0030-drops-256197},
  doi =		{10.4230/LIPIcs.ICDT.2026.5},
  annote =	{Keywords: Rule rewriting, static optimisation, static filtering, Datalog, Answer Set Programming}
}
Document
DOI: 10.4230/OASIcs.Tannen.8
AutoML for Explainable Anomaly Detection (XAD)

Authors: Nikolaos Myrtakis, Ioannis Tsamardinos, and Vassilis Christophides

Published in: OASIcs, Volume 119, The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen (2024)

Abstract
Numerous algorithms have been proposed for detecting anomalies (outliers, novelties) in an unsupervised manner. Unfortunately, it is not trivial, in general, to understand why a given sample (record) is labelled as an anomaly and thus diagnose its root causes. We propose the following reduced-dimensionality, surrogate model approach to explain detector decisions: approximate the detection model with another one that employs only a small subset of features. Subsequently, samples can be visualized in this low-dimensionality space for human understanding. To this end, we develop PROTEUS, an AutoML pipeline to produce the surrogate model, specifically designed for feature selection on imbalanced datasets. The PROTEUS surrogate model can not only explain the training data, but also the out-of-sample (unseen) data. In other words, PROTEUS produces predictive explanations by approximating the decision surface of an unsupervised detector. PROTEUS is designed to return an accurate estimate of out-of-sample predictive performance to serve as a metric of the quality of the approximation. Computational experiments confirm the efficacy of PROTEUS to produce predictive explanations for different families of detectors and to reliably estimate their predictive performance in unseen data. Unlike several ad-hoc feature importance methods, PROTEUS is robust to high-dimensional data.
Cite as

Nikolaos Myrtakis, Ioannis Tsamardinos, and Vassilis Christophides. AutoML for Explainable Anomaly Detection (XAD). In The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen. Open Access Series in Informatics (OASIcs), Volume 119, pp. 8:1-8:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{myrtakis_et_al:OASIcs.Tannen.8,
  author =	{Myrtakis, Nikolaos and Tsamardinos, Ioannis and Christophides, Vassilis},
  title =	{{AutoML for Explainable Anomaly Detection (XAD)}},
  booktitle =	{The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen},
  pages =	{8:1--8:23},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-320-1},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{119},
  editor =	{Amarilli, Antoine and Deutsch, Alin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Tannen.8},
  URN =		{urn:nbn:de:0030-drops-201049},
  doi =		{10.4230/OASIcs.Tannen.8},
  annote =	{Keywords: Anomaly Explanation, Predictive Explanation, Anomaly Interpretation, Explainable AI}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.I.9
Traffic Congestion Aware Route Assignment

Authors: Sadegh Motallebi, Hairuo Xie, Egemen Tanin, and Kotagiri Ramamohanarao

Published in: LIPIcs, Volume 177, 11th International Conference on Geographic Information Science (GIScience 2021) - Part I (2020)

Abstract
Traffic congestion emerges when traffic load exceeds the available capacity of roads. It is challenging to prevent traffic congestion in current transportation systems where vehicles tend to follow the shortest/fastest path to their destinations without considering the potential congestions caused by the concentration of vehicles. With connected autonomous vehicles, the new generation of traffic management systems can optimize traffic by coordinating the routes of all vehicles. As the connected autonomous vehicles can adhere to the routes assigned to them, the traffic management system can predict the change of traffic flow with a high level of accuracy. Based on the accurate traffic prediction and traffic congestion models, routes can be allocated in such a way that helps mitigating traffic congestions effectively. In this regard, we propose a new route assignment algorithm for the era of connected autonomous vehicles. Results show that our algorithm outperforms several baseline methods for traffic congestion mitigation.
Cite as

Sadegh Motallebi, Hairuo Xie, Egemen Tanin, and Kotagiri Ramamohanarao. Traffic Congestion Aware Route Assignment. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{motallebi_et_al:LIPIcs.GIScience.2021.I.9,
  author =	{Motallebi, Sadegh and Xie, Hairuo and Tanin, Egemen and Ramamohanarao, Kotagiri},
  title =	{{Traffic Congestion Aware Route Assignment}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{9:1--9:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.9},
  URN =		{urn:nbn:de:0030-drops-130443},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.9},
  annote =	{Keywords: Road Network, Traffic Congestion, Route Assignment, Shortest Path}
}
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