Search Results

Documents authored by Rutschmann, Daniel

Document
DOI: 10.4230/LIPIcs.ESA.2026.45
Near-Optimal Working-Set Heaps and Dijkstra on Pointer Machines

Authors: Ivor van der Hoog, John Iacono, Eva Rotenberg, and Daniel Rutschmann

Published in: LIPIcs, Volume 388, 34th Annual European Symposium on Algorithms (ESA 2026)

Abstract
A heap is a dynamic data structure that stores a set of labeled values under the following operations: pop returns the minimum value of the heap, Push(x_i) pushes a new value x_i onto the heap, and DecreaseKey(i, v) decreases the value x_i to v. A working-set heap is a heap that supports the x_i ← pop() operation in O(log Γ(x_i)) time where Γ(x_i) is the size of the working set: the number of elements that were pushed onto the heap while x_i was in the heap. The goal of working set heap design is to maintain the working set property while minimizing the overhead of the Push and DecreaseKey operations. On a word RAM, there exist working set heaps that support Push and DecreaseKey in amortized constant time. In this paper, we show via a simple construction that pointer machines, one of the most general and least-assuming computational models, support working set heaps that support Push in amortized constant time and DecreaseKey in inverse-Ackermann time. A by-product of this analysis is that Dijkstra’s shortest path algorithm can be near-universally optimal on a pointer machine - incurring only an additive O(m α(m)) overhead compared to the optimal running time for distance ordering, where m denotes the number of edges in the graph.
Cite as

Ivor van der Hoog, John Iacono, Eva Rotenberg, and Daniel Rutschmann. Near-Optimal Working-Set Heaps and Dijkstra on Pointer Machines. In 34th Annual European Symposium on Algorithms (ESA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 388, pp. 45:1-45:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{vanderhoog_et_al:LIPIcs.ESA.2026.45,
  author =	{van der Hoog, Ivor and Iacono, John and Rotenberg, Eva and Rutschmann, Daniel},
  title =	{{Near-Optimal Working-Set Heaps and Dijkstra on Pointer Machines}},
  booktitle =	{34th Annual European Symposium on Algorithms (ESA 2026)},
  pages =	{45:1--45:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-445-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{388},
  editor =	{Bille, Philip and Pettie, Seth and Storandt, Sabine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2026.45},
  URN =		{urn:nbn:de:0030-drops-271814},
  doi =		{10.4230/LIPIcs.ESA.2026.45},
  annote =	{Keywords: Data structures, graph algorithms, amortized analysis}
}
Document
DOI: 10.4230/LIPIcs.ESA.2026.101
Tight Better-Than-Worst-Case Bounds for Element Distinctness and Set Intersection

Authors: Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann

Published in: LIPIcs, Volume 388, 34th Annual European Symposium on Algorithms (ESA 2026)

Abstract
The element distinctness problem takes as input a list I of n values from a totally ordered universe, where pairwise comparisons between values are allowed, and the goal is to decide whether I contains any duplicates. It is a well-studied problem with a classical worst-case Ω(n log n) comparison-based lower bound by Fredman [TCS'76]. At first glance, this lower bound appears to rule out any algorithm more efficient than the naive approach of sorting I and comparing adjacent elements. However, upon closer inspection, the Ω(n log n) bound is overly pessimistic. For instance, if I contains n/2 identical elements, a median-finding algorithm will, regardless of the input order, find a duplicate in linear time. This raises a natural question: Are there comparison-based lower bounds for element distinctness that are sensitive to the amount of duplicates in the input instance? To address this question, we derive instance-specific lower bounds. For any input instance I, we represent the combinatorial structure of the duplicates in I by an undirected graph G(I) that connects identical elements. Each such graph G is a union of cliques, and we study algorithms by their worst-case running time over all inputs I' with G(I') ≅ G. We establish an adversarial lower bound showing that, for any deterministic algorithm 𝒜, there exists a graph G and an algorithm 𝒜' that, for all inputs I with G(I) ≅ G, is a factor O(log log n) faster than 𝒜. Consequently, no deterministic algorithm can be o(log log n)-competitive for all graphs G. We complement this with an O(log log n)-competitive deterministic algorithm, thereby obtaining tight bounds for element distinctness that go beyond classical worst-case analysis. Subsequently, we study the related problem of set intersection. We show that no deterministic set intersection algorithm can be o(log n)-competitive, and provide an O(log n)-competitive deterministic algorithm. We find it interesting and surprising to discover tight O(log log n)-competitive bounds for element distinctness. Moreover, we find the separation between element distinctness and the set intersection problem unexpected.
Cite as

Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann. Tight Better-Than-Worst-Case Bounds for Element Distinctness and Set Intersection. In 34th Annual European Symposium on Algorithms (ESA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 388, pp. 101:1-101:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{vanderhoog_et_al:LIPIcs.ESA.2026.101,
  author =	{van der Hoog, Ivor and Rotenberg, Eva and Rutschmann, Daniel},
  title =	{{Tight Better-Than-Worst-Case Bounds for Element Distinctness and Set Intersection}},
  booktitle =	{34th Annual European Symposium on Algorithms (ESA 2026)},
  pages =	{101:1--101:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-445-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{388},
  editor =	{Bille, Philip and Pettie, Seth and Storandt, Sabine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2026.101},
  URN =		{urn:nbn:de:0030-drops-272372},
  doi =		{10.4230/LIPIcs.ESA.2026.101},
  annote =	{Keywords: Comparison-based analysis, set intersection, universal optimality}
}
Document
DOI: 10.4230/LIPIcs.ESA.2026.106
Instance Optimal and Universally Optimal Bounds for Imprecise Pareto Fronts

Authors: Sarita de Berg, Nynne Maria Foldager Bække, Frida Astrup Eriksen, Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann

Published in: LIPIcs, Volume 388, 34th Annual European Symposium on Algorithms (ESA 2026)

Abstract
In the imprecise geometry model, the input is a family of regions F = (R₁, R₂, …,R_n), each containing a point p_i ∈ R_i. The task is then to compute some function of the points p₁,p₂,… p_n, in our case an implicit representation of their Pareto front. To this end, one may query a region R_i to retrieve its contained point p_i ∈ R_i. In this model, efficiency is interpreted in two ways: minimizing (i) the number of retrievals, and (ii) the computation time both for preprocessing, and the execution of the query stage, i.e. for computing which points to query and constructing the output. We present an algorithm to construct (an implicit representation of) the Pareto front for possibly overlapping rectangles, that is instance-optimal with respect to the number of retrievals. This means that for every fixed input (F, P), there is no algorithm that retrieves asymptotically fewer regions to compute the output. This is a strong algorithmic quality, as it means that our algorithm is competitive even to clairvoyant algorithms which only have to verify the correctness of a correct guess. In terms of algorithmic running time, instance-optimality is provably unobtainable. We instead present an algorithm which is within a log n-factor of instance optimality. This generalizes earlier results which assumed the regions to not overlap, at only a minor cost in running time. For unit squares, we present an algorithm that is not only instance optimal in the number of retrievals, but also universally optimal in terms of running time. This means that for any fixed set of regions F, no algorithm has a better worst-case running time for all possible point sets P. Thus, this work presents the first universally optimal algorithm for overlapping planar input. Compared to previous work, our result improves the degree to which the input regions may overlap, the preprocessing time, the number of retrievals, and the running time.
Cite as

Sarita de Berg, Nynne Maria Foldager Bække, Frida Astrup Eriksen, Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann. Instance Optimal and Universally Optimal Bounds for Imprecise Pareto Fronts. In 34th Annual European Symposium on Algorithms (ESA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 388, pp. 106:1-106:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{deberg_et_al:LIPIcs.ESA.2026.106,
  author =	{de Berg, Sarita and B{\ae}kke, Nynne Maria Foldager and Eriksen, Frida Astrup and van der Hoog, Ivor and Rotenberg, Eva and Rutschmann, Daniel},
  title =	{{Instance Optimal and Universally Optimal Bounds for Imprecise Pareto Fronts}},
  booktitle =	{34th Annual European Symposium on Algorithms (ESA 2026)},
  pages =	{106:1--106:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-445-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{388},
  editor =	{Bille, Philip and Pettie, Seth and Storandt, Sabine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2026.106},
  URN =		{urn:nbn:de:0030-drops-272426},
  doi =		{10.4230/LIPIcs.ESA.2026.106},
  annote =	{Keywords: Pareto front, imprecise geometry, instance optimality, universal optimality, preprocessing model, partial information}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.25
Instance-Optimal Imprecise Convex Hull

Authors: Sarita de Berg, Ivor van der Hoog, Eva Rotenberg, Daniel Rutschmann, and Sampson Wong

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

Abstract
Imprecise measurements of a point set P = (p₁, …, p_n) can be modelled by a family of regions F = (R₁, …, R_n), where each imprecise region R_i ∈ F contains a unique point p_i ∈ P. A retrieval models an accurate measurement by replacing an imprecise region R_i with its corresponding point p_i. We construct the convex hull of an imprecise point set in the plane, by determining the cyclic ordering of the convex hull vertices of P as efficiently as possible. Efficiency is interpreted in two ways: (i) minimising the number of retrievals, and (ii) the computation time to determine the set of regions that must be retrieved. Previous works focused on only one of these two aspects: either minimising retrievals or optimising algorithmic runtime. Our contribution is the first to simultaneously achieve both. Let r(F, P) denote the minimal number of retrievals required by any algorithm to determine the convex hull of P for a given instance (F, P). For a family F of n constant-complexity polygons, our main result is a reconstruction algorithm that performs Θ(r(F, P)) retrievals in O(r(F, P) log³ n) time. Compared to previous approaches that achieve optimal retrieval counts, we improve the runtime per retrieval from polynomial to polylogarithmic. We extend the generality of previous results to simple k-gons, to pairwise disjoint disks with radii in [1,k], and to unit disks where at most k disks overlap in a single point. Our runtime scales linearly with k.
Cite as

Sarita de Berg, Ivor van der Hoog, Eva Rotenberg, Daniel Rutschmann, and Sampson Wong. Instance-Optimal Imprecise Convex Hull. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 25:1-25:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{deberg_et_al:LIPIcs.ESA.2025.25,
  author =	{de Berg, Sarita and van der Hoog, Ivor and Rotenberg, Eva and Rutschmann, Daniel and Wong, Sampson},
  title =	{{Instance-Optimal Imprecise Convex Hull}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{25:1--25:15},
  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.2025.25},
  URN =		{urn:nbn:de:0030-drops-244932},
  doi =		{10.4230/LIPIcs.ESA.2025.25},
  annote =	{Keywords: convex hull, imprecise geometry preprocessing model, partial information}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.71
Simpler Universally Optimal Dijkstra

Authors: Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann

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

Abstract
Let G be a weighted (directed) graph with n vertices and m edges. Given a source vertex s, Dijkstra’s algorithm computes the shortest path lengths from s to all other vertices in O(m + n log n) time. This bound is known to be worst-case optimal via a reduction to sorting. Theoretical computer science has developed numerous fine-grained frameworks for analyzing algorithmic performance beyond standard worst-case analysis, such as instance optimality and output sensitivity. Haeupler, Hladík, Rozhoň, Tarjan, and Tětek [FOCS '24] consider the notion of universal optimality, a refined complexity measure that accounts for both the graph topology and the edge weights. For a fixed graph topology, the universal running time of a weighted graph algorithm is defined as its worst-case running time over all possible edge weightings of G. An algorithm is universally optimal if no other algorithm achieves a better asymptotic universal running time on any particular graph topology. Haeupler, Hladík, Rozhoň, Tarjan, and Tětek show that Dijkstra’s algorithm can be made universally optimal by replacing the heap with a custom data structure. Their approach builds on Iacono’s [SWAT '00] working-set bound ϕ(x). This is a technical definition that, intuitively, for a heap element x, counts the maximum number of simultaneously-present elements y that were pushed onto the heap whilst x was in the heap. They design a new heap data structure that can pop an element x in O(1 + log ϕ(x)) time. They show that Dijkstra’s algorithm with their heap data structure is universally optimal. In this work, we revisit their result. We use a simpler heap property that we will call timestamp optimality, where the cost of popping an element x is logarithmic in the number of elements inserted between pushing and popping x. We show that timestamp optimal heaps are not only easier to define but also easier to implement. Using these time stamps, we provide a significantly simpler proof that Dijkstra’s algorithm, with the right kind of heap, is universally optimal.
Cite as

Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann. Simpler Universally Optimal Dijkstra. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 71:1-71:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{vanderhoog_et_al:LIPIcs.ESA.2025.71,
  author =	{van der Hoog, Ivor and Rotenberg, Eva and Rutschmann, Daniel},
  title =	{{Simpler Universally Optimal Dijkstra}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{71:1--71:9},
  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.2025.71},
  URN =		{urn:nbn:de:0030-drops-245390},
  doi =		{10.4230/LIPIcs.ESA.2025.71},
  annote =	{Keywords: Graph algorithms, instance optimality, Fibonnacci heaps, simplification}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.102
A Combinatorial Proof of Universal Optimality for Computing a Planar Convex Hull

Authors: Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann

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

Abstract
For a planar point set P, its convex hull is the smallest convex polygon that encloses all points in P. The construction of the convex hull from an array I_P containing P is a fundamental problem in computational geometry. By sorting I_P in lexicographical order, one can construct the convex hull of P in O(n log n) time which is worst-case optimal. Standard worst-case analysis, however, has been criticized as overly coarse or pessimistic, and researchers search for more refined analyses. For an algorithm A, worst-case analysis fixes n, and considers the maximum running time of A across all size-n point sets P and permutations I_P of P. Output-sensitive analysis fixes n and k, and considers the maximum running time across all size-n points sets P with k hull points and permutations I_P of P. Universal analysis provides an even stronger guarantee. It fixes a point set P and considers the maximum running time across all permutations I_P of P. Kirkpatrick, McQueen, and Seidel [SICOMP'86] consider output-sensitive analysis. If the convex hull of P contains k points, then their algorithm runs in O(n log k) time. Afshani, Barbay, Chan [FOCS'07] prove that the algorithm by Kirkpatrick, McQueen, and Seidel is also universally optimal. Their proof restricts the model of computation to any algebraic decision tree model where the test functions have at most constant degree and at most a constant number of arguments. They rely upon involved algebraic arguments to construct a lower bound for each point set P that matches the universal running time of [SICOMP'86]. We provide a different proof of universal optimality. Instead of restricting the computational model, we further specify the output. We require as output (1) the convex hull, and (2) for each internal point of P a witness for it being internal. Our argument is shorter, perhaps simpler, and applicable in more general models of computation.
Cite as

Ivor van der Hoog, Eva Rotenberg, and Daniel Rutschmann. A Combinatorial Proof of Universal Optimality for Computing a Planar Convex Hull. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 102:1-102:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{vanderhoog_et_al:LIPIcs.ESA.2025.102,
  author =	{van der Hoog, Ivor and Rotenberg, Eva and Rutschmann, Daniel},
  title =	{{A Combinatorial Proof of Universal Optimality for Computing a Planar Convex Hull}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{102:1--102:13},
  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.2025.102},
  URN =		{urn:nbn:de:0030-drops-245715},
  doi =		{10.4230/LIPIcs.ESA.2025.102},
  annote =	{Keywords: Convex hull, Combinatorial proofs, Universal optimality}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.78
Efficient Greedy Discrete Subtrajectory Clustering

Authors: Ivor van der Hoog, Lara Ost, Eva Rotenberg, and Daniel Rutschmann

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
We cluster a set of trajectories 𝒯 using subtrajectories of 𝒯. We require for a clustering C that any two subtrajectories (𝒯[a, b], 𝒯[c, d]) in a cluster have disjoint intervals [a,b] and [c, d]. Clustering quality may be measured by the number of clusters, the number of vertices of 𝒯 that are absent from the clustering, and by the Fréchet distance between subtrajectories in a cluster. A Δ-cluster of 𝒯 is a cluster 𝒫 of subtrajectories of 𝒯 with a centre P ∈ 𝒫, where all subtrajectories in 𝒫 have Fréchet distance at most Δ to P. Buchin, Buchin, Gudmundsson, Löffler and Luo present two O(n² + n m 𝓁)-time algorithms: SC(max, 𝓁, Δ, 𝒯) computes a single Δ-cluster where P has at least 𝓁 vertices and maximises the cardinality m of 𝒫. SC(m, max, Δ, 𝒯) computes a single Δ-cluster where 𝒫 has cardinality m and maximises the complexity 𝓁 of P. In this paper, which is a mixture of algorithms engineering and theoretical insights, we use such maximum-cardinality clusters in a greedy clustering algorithm. We first provide an efficient implementation of SC(max, 𝓁, Δ, 𝒯) and SC(m, max, Δ, 𝒯) that significantly outperforms previous implementations. Next, we use these functions as a subroutine in a greedy clustering algorithm, which performs well when compared to existing subtrajectory clustering algorithms on real-world data. Finally, we observe that, for fixed Δ and 𝒯, these two functions always output a point on the Pareto front of some bivariate function θ(𝓁, m). We design a new algorithm PSC(Δ, 𝒯) that in O(n² log⁴ n) time computes a 2-approximation of this Pareto front. This yields a broader set of candidate clusters, with comparable quality to the output of the previous functions. We show that using PSC(Δ, 𝒯) as a subroutine improves the clustering quality and performance even further.
Cite as

Ivor van der Hoog, Lara Ost, Eva Rotenberg, and Daniel Rutschmann. Efficient Greedy Discrete Subtrajectory Clustering. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 78:1-78:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{vanderhoog_et_al:LIPIcs.SoCG.2025.78,
  author =	{van der Hoog, Ivor and Ost, Lara and Rotenberg, Eva and Rutschmann, Daniel},
  title =	{{Efficient Greedy Discrete Subtrajectory Clustering}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{78:1--78:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.78},
  URN =		{urn:nbn:de:0030-drops-232308},
  doi =		{10.4230/LIPIcs.SoCG.2025.78},
  annote =	{Keywords: Algorithms engineering, Fr\'{e}chet distance, subtrajectory clustering}
}
Document
DOI: 10.4230/LIPIcs.STACS.2023.37
Approximate Selection with Unreliable Comparisons in Optimal Expected Time

Authors: Shengyu Huang, Chih-Hung Liu, and Daniel Rutschmann

Published in: LIPIcs, Volume 254, 40th International Symposium on Theoretical Aspects of Computer Science (STACS 2023)

Abstract
Given n elements, an integer k ≤ n/2 and a parameter ε ≥ 1/n, we study the problem of selecting an element with rank in (k-nε, k+nε] using unreliable comparisons where the outcome of each comparison is incorrect independently with a constant error probability, and multiple comparisons between the same pair of elements are independent. In this fault model, the fundamental problems of finding the minimum, selecting the k-th smallest element and sorting have been shown to require Θ(n log 1/Q), Θ(n log k/Q) and Θ(n log n/Q) comparisons, respectively, to achieve success probability 1-Q [Uriel Feige et al., 1994]. Considering the increasing complexity of modern computing, it is of great interest to develop approximation algorithms that enable a trade-off between the solution quality and the number of comparisons. In particular, approximation algorithms would even be able to attain a sublinear number of comparisons. Very recently, Leucci and Liu [Stefano Leucci and Chih-Hung Liu, 2022] proved that the approximate minimum selection problem, which covers the case that k ≤ nε, requires expected Θ(ε^{-1} log 1/Q) comparisons, but the general case, i.e., for nε < k ≤ n/2, is still open. We develop a randomized algorithm that performs expected O(k/n ε^{-2} log 1/Q) comparisons to achieve success probability at least 1-Q. For k = n ε, the number of comparisons is O(ε^{-1} log 1/Q), matching Leucci and Liu’s result [Stefano Leucci and Chih-Hung Liu, 2022], whereas for k = n/2 (i.e., approximating the median), the number of comparisons is O(ε^{-2} log 1/Q). We also prove that even in the absence of comparison faults, any randomized algorithm with success probability at least 1-Q performs expected Ω(min{n, k/n ε^{-2} log 1/Q}) comparisons. As long as n is large enough, i.e., when n = Ω(k/n ε^{-2} log 1/Q), our lower bound demonstrates the optimality of our algorithm, which covers the possible range of attaining a sublinear number of comparisons. Surprisingly, for constant Q, our algorithm performs expected O(k/n ε^{-2}) comparisons, matching the best possible approximation algorithm in the absence of computation faults. In contrast, for the exact selection problem, the expected number of comparisons is Θ(n log k) with faults versus Θ(n) without faults. Our results also indicate a clear distinction between approximating the minimum and approximating the k-th smallest element, which holds even for the high probability guarantee, e.g., if k = n/2, Q = 1/n and ε = n^{-α} for α ∈ (0, 1/2), the asymptotic difference is almost quadratic, i.e., Θ̃(n^α) versus Θ̃(n^{2α}).
Cite as

Shengyu Huang, Chih-Hung Liu, and Daniel Rutschmann. Approximate Selection with Unreliable Comparisons in Optimal Expected Time. In 40th International Symposium on Theoretical Aspects of Computer Science (STACS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 254, pp. 37:1-37:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{huang_et_al:LIPIcs.STACS.2023.37,
  author =	{Huang, Shengyu and Liu, Chih-Hung and Rutschmann, Daniel},
  title =	{{Approximate Selection with Unreliable Comparisons in Optimal Expected Time}},
  booktitle =	{40th International Symposium on Theoretical Aspects of Computer Science (STACS 2023)},
  pages =	{37:1--37:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-266-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{254},
  editor =	{Berenbrink, Petra and Bouyer, Patricia and Dawar, Anuj and Kant\'{e}, Mamadou Moustapha},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2023.37},
  URN =		{urn:nbn:de:0030-drops-176898},
  doi =		{10.4230/LIPIcs.STACS.2023.37},
  annote =	{Keywords: Approximate Selection, Unreliable Comparisons, Independent Faults}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2022.59
Chains, Koch Chains, and Point Sets with Many Triangulations

Authors: Daniel Rutschmann and Manuel Wettstein

Published in: LIPIcs, Volume 224, 38th International Symposium on Computational Geometry (SoCG 2022)

Abstract
We introduce the abstract notion of a chain, which is a sequence of n points in the plane, ordered by x-coordinates, so that the edge between any two consecutive points is unavoidable as far as triangulations are concerned. A general theory of the structural properties of chains is developed, alongside a general understanding of their number of triangulations. We also describe an intriguing new and concrete configuration, which we call the Koch chain due to its similarities to the Koch curve. A specific construction based on Koch chains is then shown to have Ω(9.08ⁿ) triangulations. This is a significant improvement over the previous and long-standing lower bound of Ω(8.65ⁿ) for the maximum number of triangulations of planar point sets.
Cite as

Daniel Rutschmann and Manuel Wettstein. Chains, Koch Chains, and Point Sets with Many Triangulations. In 38th International Symposium on Computational Geometry (SoCG 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 224, pp. 59:1-59:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{rutschmann_et_al:LIPIcs.SoCG.2022.59,
  author =	{Rutschmann, Daniel and Wettstein, Manuel},
  title =	{{Chains, Koch Chains, and Point Sets with Many Triangulations}},
  booktitle =	{38th International Symposium on Computational Geometry (SoCG 2022)},
  pages =	{59:1--59:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-227-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{224},
  editor =	{Goaoc, Xavier and Kerber, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2022.59},
  URN =		{urn:nbn:de:0030-drops-160678},
  doi =		{10.4230/LIPIcs.SoCG.2022.59},
  annote =	{Keywords: Planar Point Set, Chain, Koch Chain, Triangulation, Maximum Number of Triangulations, Lower Bound}
}

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact