20 Search Results for "Schewior, Kevin"

Document
DOI: 10.4230/DagRep.15.3.159
Approximation Algorithms for Stochastic Optimization (Dagstuhl Seminar 25132)

Authors: Lisa Hellerstein, Viswanath Nagarajan, and Kevin Schewior

Published in: Dagstuhl Reports, Volume 15, Issue 3 (2025)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25132 "Approximation Algorithms for Stochastic Optimization". In this seminar, we gathered researchers from different areas interested in combinatorial optimization problems in which there is some stochasticity in the input. The focus was on approximation algorithms for computing adaptive or non-adaptive strategies to interact with this stochastic uncertainty as well as structural measures such as the adaptivity gap.
Cite as

Lisa Hellerstein, Viswanath Nagarajan, and Kevin Schewior. Approximation Algorithms for Stochastic Optimization (Dagstuhl Seminar 25132). In Dagstuhl Reports, Volume 15, Issue 3, pp. 159-176, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@Article{hellerstein_et_al:DagRep.15.3.159,
  author =	{Hellerstein, Lisa and Nagarajan, Viswanath and Schewior, Kevin},
  title =	{{Approximation Algorithms for Stochastic Optimization (Dagstuhl Seminar 25132)}},
  pages =	{159--176},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2025},
  volume =	{15},
  number =	{3},
  editor =	{Hellerstein, Lisa and Nagarajan, Viswanath and Schewior, Kevin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.3.159},
  URN =		{urn:nbn:de:0030-drops-248959},
  doi =		{10.4230/DagRep.15.3.159},
  annote =	{Keywords: adaptivity, approximation algorithms, combinatorial optimization, stochastic optimization}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.52
Beating Competitive Ratio 4 for Graphic Matroid Secretary

Authors: Kiarash Banihashem, MohammadTaghi Hajiaghayi, Dariusz R. Kowalski, Piotr Krysta, Danny Mittal, and Jan Olkowski

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

Abstract
One of the classic problems in online decision-making is the secretary problem, where the goal is to hire the best secretary out of n rankable applicants or, in a natural extension, to maximize the probability of selecting the largest number from a sequence arriving in random order. Many works have considered generalizations of this problem where one can accept multiple values subject to a combinatorial constraint. The seminal work of Babaioff, Immorlica, Kempe, and Kleinberg (SODA'07, JACM'18) proposed the matroid secretary conjecture, suggesting that there exists an O(1)-competitive algorithm for the matroid constraint, and many works since have attempted to obtain algorithms for both general matroids and specific classes of matroids. The ultimate goal of these results is to obtain an e-competitive algorithm, and the strong matroid secretary conjecture states that this is possible for general matroids. One of the most important classes of matroids is the graphic matroid, where a set of edges in a graph is deemed independent if it contains no cycle. Given the rich combinatorial structure of graphs, obtaining algorithms for these matroids is often seen as a good first step towards solving the problem for general matroids. For matroid secretary, Babaioff et al. (SODA'07, JACM'18) first studied graphic matroid case and obtained a 16-competitive algorithm. Subsequent works have improved the competitive ratio, most recently to 4 by Soto, Turkieltaub, and Verdugo (SODA'18). In this paper, we break the 4-competitive barrier for the problem, obtaining a new algorithm with a competitive ratio of 3.95. For the special case of simple graphs (i.e., graphs that do not contain parallel edges) we further improve this to 3.77. Intuitively, solving the problem for simple graphs is easier as they do not contain cycles of length two. A natural question that arises is whether we can obtain a ratio arbitrarily close to e by assuming the graph has a large enough girth. We answer this question affirmatively, proving that one can obtain a competitive ratio arbitrarily close to e even for constant values of girth, providing further evidence for the strong matroid secretary conjecture. We further show that this bound is tight: for any constant g, one cannot obtain a competitive ratio better than e even if we assume that the input graph has girth at least g. To our knowledge, such a bound was not previously known even for simple graphs.
Cite as

Kiarash Banihashem, MohammadTaghi Hajiaghayi, Dariusz R. Kowalski, Piotr Krysta, Danny Mittal, and Jan Olkowski. Beating Competitive Ratio 4 for Graphic Matroid Secretary. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 52:1-52:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{banihashem_et_al:LIPIcs.ESA.2025.52,
  author =	{Banihashem, Kiarash and Hajiaghayi, MohammadTaghi and Kowalski, Dariusz R. and Krysta, Piotr and Mittal, Danny and Olkowski, Jan},
  title =	{{Beating Competitive Ratio 4 for Graphic Matroid Secretary}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{52:1--52:16},
  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.2025.52},
  URN =		{urn:nbn:de:0030-drops-245205},
  doi =		{10.4230/LIPIcs.ESA.2025.52},
  annote =	{Keywords: online algorithms, graphic matroids, secretary problem}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.92
Incremental Maximization for a Broad Class of Objectives

Authors: Yann Disser and David Weckbecker

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

Abstract
We consider incremental maximization problems, where the solution has to be built up gradually by adding elements one after the other. In every step, the incremental solution must be competitive, compared against the optimum solution of the current cardinality. We prove that a competitive solution always exists when the objective function is monotone and β-accountable, by providing a scaling algorithm that guarantees a constant competitive ratio. This generalizes known results and, importantly, yields the first competitive algorithm for the natural class of monotone and subadditive objective functions.
Cite as

Yann Disser and David Weckbecker. Incremental Maximization for a Broad Class of Objectives. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 92:1-92:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{disser_et_al:LIPIcs.ESA.2025.92,
  author =	{Disser, Yann and Weckbecker, David},
  title =	{{Incremental Maximization for a Broad Class of Objectives}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{92:1--92:13},
  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.2025.92},
  URN =		{urn:nbn:de:0030-drops-245613},
  doi =		{10.4230/LIPIcs.ESA.2025.92},
  annote =	{Keywords: incremental maximization, competitive analysis, subadditive functions}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2025.26
Non-Adaptive Evaluation of k-of- n Functions: Tight Gap and a Unit-Cost PTAS

Authors: Mads Anker Nielsen, Lars Rohwedder, and Kevin Schewior

Published in: LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)

Abstract
We consider the Stochastic Boolean Function Evaluation (SBFE) problem in the well-studied case of k-of-n functions: There are independent Boolean random variables x_1,… ,x_n where each variable i has a known probability p_i of taking value 1, and a known cost c_i that can be paid to find out its value. The value of the function is 1 iff there are at least k 1s among the variables. The goal is to efficiently compute a strategy that, at minimum expected cost, tests the variables until the function value is determined. While an elegant polynomial-time exact algorithm is known when tests can be made adaptively, we focus on the non-adaptive variant, for which much less is known. First, we show a clean and tight lower bound of 2 on the adaptivity gap, i.e., the worst-case multiplicative loss in the objective function caused by disallowing adaptivity, of the problem. This improves the tight lower bound of 3/2 for the unit-cost variant. Second, we give a PTAS for computing the best non-adaptive strategy in the unit-cost case, the first PTAS for an SBFE problem. At the core, our scheme establishes a novel notion of two-sided dominance (w.r.t. the optimal solution) by guessing so-called milestone tests for a set of carefully chosen buckets of tests. To turn this technique into a polynomial-time algorithm, we use a decomposition approach paired with a random-shift argument.
Cite as

Mads Anker Nielsen, Lars Rohwedder, and Kevin Schewior. Non-Adaptive Evaluation of k-of- n Functions: Tight Gap and a Unit-Cost PTAS. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 353, pp. 26:1-26:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{nielsen_et_al:LIPIcs.APPROX/RANDOM.2025.26,
  author =	{Nielsen, Mads Anker and Rohwedder, Lars and Schewior, Kevin},
  title =	{{Non-Adaptive Evaluation of k-of- n Functions: Tight Gap and a Unit-Cost PTAS}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)},
  pages =	{26:1--26:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-397-3},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{353},
  editor =	{Ene, Alina and Chattopadhyay, Eshan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.26},
  URN =		{urn:nbn:de:0030-drops-243920},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2025.26},
  annote =	{Keywords: Approximation scheme, Boolean functions, stochastic combinatorial optimization, stochastic function evaluation, sequential testing, adaptivity}
}
Document
DOI: 10.4230/LIPIcs.WADS.2025.41
Scheduling on Identical Machines with Setup Time and Unknown Execution Time

Authors: Yasushi Kawase, Kazuhisa Makino, Vinh Long Phan, and Hanna Sumita

Published in: LIPIcs, Volume 349, 19th International Symposium on Algorithms and Data Structures (WADS 2025)

Abstract
In this study, we investigate a scheduling problem on identical machines in which jobs require initial setup before execution. We assume that an algorithm can dynamically form a batch (i.e., a collection of jobs to be processed together) from the remaining jobs. The setup time is modeled as a known monotone function of the set of jobs within a batch, while the execution time of each job remains unknown until completion. This uncertainty poses significant challenges for minimizing the makespan. We address these challenges by considering two scenarios: each job batch must be assigned to a single machine, or a batch may be distributed across multiple machines. For both scenarios, we analyze settings with and without preemption. Across these four settings, we design online algorithms that achieve asymptotically optimal competitive ratios with respect to both the number of jobs and the number of machines.
Cite as

Yasushi Kawase, Kazuhisa Makino, Vinh Long Phan, and Hanna Sumita. Scheduling on Identical Machines with Setup Time and Unknown Execution Time. In 19th International Symposium on Algorithms and Data Structures (WADS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 349, pp. 41:1-41:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{kawase_et_al:LIPIcs.WADS.2025.41,
  author =	{Kawase, Yasushi and Makino, Kazuhisa and Phan, Vinh Long and Sumita, Hanna},
  title =	{{Scheduling on Identical Machines with Setup Time and Unknown Execution Time}},
  booktitle =	{19th International Symposium on Algorithms and Data Structures (WADS 2025)},
  pages =	{41:1--41:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-398-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{349},
  editor =	{Morin, Pat and Oh, Eunjin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WADS.2025.41},
  URN =		{urn:nbn:de:0030-drops-242728},
  doi =		{10.4230/LIPIcs.WADS.2025.41},
  annote =	{Keywords: Online scheduling, Competitive analysis, Makespan minimization, Identical machines scheduling}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2025.15
Analysis of EDF for Real-Time Multiprocessor Systems with Resource Sharing

Authors: Kunal Agrawal, Sanjoy Baruah, Jeremy T. Fineman, Alberto Marchetti-Spaccamela, and Jinhao Zhao

Published in: LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)

Abstract
The classic Earliest Deadline First (EDF) algorithm is widely studied and used due to its simplicity and strong theoretical performance, but has not been rigorously analyzed for systems where jobs may execute critical sections protected by shared locks. Analyzing such systems is often challenging due to unpredictable delays caused by contention. In this paper, we propose a straightforward generalization of EDF, called EDF-Block. In this generalization, the critical sections are executed non-preemptively, but scheduling and lock acquisition priorities are based on EDF. We establish lower bounds on the speed augmentation required for any non-clairvoyant scheduler (EDF-Block is an example of non-clairvoyant schedulers) and for EDF-Block, showing that EDF-Block requires at least 4.11× speed augmentation for jobs and 4× for tasks. We then provide an upper bound analysis, demonstrating that EDF-Block requires speedup of at most 6 to schedule all feasible job and task sets.
Cite as

Kunal Agrawal, Sanjoy Baruah, Jeremy T. Fineman, Alberto Marchetti-Spaccamela, and Jinhao Zhao. Analysis of EDF for Real-Time Multiprocessor Systems with Resource Sharing. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 15:1-15:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{agrawal_et_al:LIPIcs.ECRTS.2025.15,
  author =	{Agrawal, Kunal and Baruah, Sanjoy and Fineman, Jeremy T. and Marchetti-Spaccamela, Alberto and Zhao, Jinhao},
  title =	{{Analysis of EDF for Real-Time Multiprocessor Systems with Resource Sharing}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{15:1--15:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-377-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{335},
  editor =	{Mancuso, Renato},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.15},
  URN =		{urn:nbn:de:0030-drops-235932},
  doi =		{10.4230/LIPIcs.ECRTS.2025.15},
  annote =	{Keywords: Real-Time Scheduling, Non-Clairvoyant Scheduling, EDF, Competitive Analysis, Shared Resources}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.8
Identifying Approximate Minimizers Under Stochastic Uncertainity

Authors: Hessa Al-Thani and Viswanath Nagarajan

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
We study a fundamental stochastic selection problem involving n independent random variables, each of which can be queried at some cost. Given a tolerance level δ, the goal is to find a δ-approximately minimum (or maximum) value over all the random variables, at minimum expected cost. A solution to this problem is an adaptive sequence of queries, where the choice of the next query may depend on previously-observed values. Two variants arise, depending on whether the goal is to find a δ-minimum value or a δ-minimizer. When all query costs are uniform, we provide a 4-approximation algorithm for both variants. When query costs are non-uniform, we provide a 5.83-approximation algorithm for the δ-minimum value and a 7.47-approximation for the δ-minimizer. All our algorithms rely on non-adaptive policies (that perform a fixed sequence of queries), so we also upper bound the corresponding "adaptivity" gaps. Our analysis relates the stopping probabilities in the algorithm and optimal policies, where a key step is in proving and using certain stochastic dominance properties.
Cite as

Hessa Al-Thani and Viswanath Nagarajan. Identifying Approximate Minimizers Under Stochastic Uncertainity. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 8:1-8:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{althani_et_al:LIPIcs.ICALP.2025.8,
  author =	{Al-Thani, Hessa and Nagarajan, Viswanath},
  title =	{{Identifying Approximate Minimizers Under Stochastic Uncertainity}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{8:1--8:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.8},
  URN =		{urn:nbn:de:0030-drops-233854},
  doi =		{10.4230/LIPIcs.ICALP.2025.8},
  annote =	{Keywords: Approximation algorithms, stochastic optimization, selection problem}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.53
A PTAS for TSP with Neighbourhoods over Parallel Line Segments

Authors: Benyamin Ghaseminia and Mohammad R. Salavatipour

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

Abstract
We consider the Travelling Salesman Problem with Neighbourhoods (TSPN) on the Euclidean plane (ℝ²) and present a Polynomial-Time Approximation Scheme (PTAS) when the neighbourhoods are parallel line segments with lengths between [1, λ] for any constant value λ ≥ 1. In TSPN (which generalizes classic TSP), each client represents a set (or neighbourhood) of points in a metric and the goal is to find a minimum cost TSP tour that visits at least one point from each client set. In the Euclidean setting, each neighbourhood is a region on the plane. TSPN is significantly more difficult than classic TSP even in the Euclidean setting, as it captures group TSP. A notable case of TSPN is when each neighbourhood is a line segment. Although there are PTASs for when neighbourhoods are fat objects (with limited overlap), TSPN over line segments is APX-hard even if all the line segments have unit length. For parallel (unit) line segments, the best approximation factor is 3√2 from more than two decades ago. The PTAS we present in this paper settles the approximability of this case of the problem. Our algorithm finds a (1 + ε)-factor approximation for an instance of the problem for n segments with lengths in [1,λ] in time n^O(λ/ε³).
Cite as

Benyamin Ghaseminia and Mohammad R. Salavatipour. A PTAS for TSP with Neighbourhoods over Parallel Line Segments. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 53:1-53:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{ghaseminia_et_al:LIPIcs.SoCG.2025.53,
  author =	{Ghaseminia, Benyamin and Salavatipour, Mohammad R.},
  title =	{{A PTAS for TSP with Neighbourhoods over Parallel Line Segments}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{53:1--53:15},
  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.2025.53},
  URN =		{urn:nbn:de:0030-drops-232058},
  doi =		{10.4230/LIPIcs.SoCG.2025.53},
  annote =	{Keywords: Approximation Scheme, TSP Neighbourhood, Parallel line segments}
}
Document
DOI: 10.4230/LIPIcs.STACS.2025.50
Designing Exploration Contracts

Authors: Martin Hoefer, Conrad Schecker, and Kevin Schewior

Published in: LIPIcs, Volume 327, 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025)

Abstract
We study a natural application of contract design in the context of sequential exploration problems. In our principal-agent setting, a search task is delegated to an agent. The agent performs a sequential exploration of n boxes, suffers the exploration cost for each inspected box, and selects the content (called the prize) of one inspected box as outcome. Agent and principal obtain an individual value based on the selected prize. To influence the search, the principal a-priori designs a contract with a non-negative payment to the agent for each potential prize. The goal of the principal is to maximize her expected reward, i.e., value minus payment. Interestingly, this natural contract scenario shares close relations with the Pandora’s Box problem. We show how to compute optimal contracts for the principal in several scenarios. A popular and important subclass is that of linear contracts, and we show how to compute optimal linear contracts in polynomial time. For general contracts, we obtain optimal contracts under the standard assumption that the agent suffers cost but obtains value only from the transfers by the principal. More generally, for general contracts with non-zero agent values for outcomes we show how to compute an optimal contract in two cases: (1) when each box has only one prize with non-zero value for principal and agent, (2) for i.i.d. boxes with a single prize with positive value for the principal.
Cite as

Martin Hoefer, Conrad Schecker, and Kevin Schewior. Designing Exploration Contracts. In 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 327, pp. 50:1-50:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{hoefer_et_al:LIPIcs.STACS.2025.50,
  author =	{Hoefer, Martin and Schecker, Conrad and Schewior, Kevin},
  title =	{{Designing Exploration Contracts}},
  booktitle =	{42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025)},
  pages =	{50:1--50:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-365-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{327},
  editor =	{Beyersdorff, Olaf and Pilipczuk, Micha{\l} and Pimentel, Elaine and Thắng, Nguy\~{ê}n Kim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2025.50},
  URN =		{urn:nbn:de:0030-drops-228755},
  doi =		{10.4230/LIPIcs.STACS.2025.50},
  annote =	{Keywords: Exploration, Contract Design, Pandora’s Box Problem}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2024.14
Scheduling on a Stochastic Number of Machines

Authors: Moritz Buchem, Franziska Eberle, Hugo Kooki Kasuya Rosado, Kevin Schewior, and Andreas Wiese

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

Abstract
We consider a new scheduling problem on parallel identical machines in which the number of machines is initially not known, but it follows a given probability distribution. Only after all jobs are assigned to a given number of bags, the actual number of machines is revealed. Subsequently, the jobs need to be assigned to the machines without splitting the bags. This is the stochastic version of a related problem introduced by Stein and Zhong [SODA 2018, TALG 2020] and it is, for example, motivated by bundling jobs that need to be scheduled by data centers. We present two PTASs for the stochastic setting, computing job-to-bag assignments that (i) minimize the expected maximum machine load and (ii) maximize the expected minimum machine load (like in the Santa Claus problem), respectively. The former result follows by careful enumeration combined with known PTASs. For the latter result, we introduce an intricate dynamic program that we apply to a suitably rounded instance.
Cite as

Moritz Buchem, Franziska Eberle, Hugo Kooki Kasuya Rosado, Kevin Schewior, and Andreas Wiese. Scheduling on a Stochastic Number of Machines. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 317, pp. 14:1-14:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@InProceedings{buchem_et_al:LIPIcs.APPROX/RANDOM.2024.14,
  author =	{Buchem, Moritz and Eberle, Franziska and Kasuya Rosado, Hugo Kooki and Schewior, Kevin and Wiese, Andreas},
  title =	{{Scheduling on a Stochastic Number of Machines}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)},
  pages =	{14:1--14:15},
  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.2024.14},
  URN =		{urn:nbn:de:0030-drops-210073},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2024.14},
  annote =	{Keywords: scheduling, approximation algorithms, stochastic machines, makespan, max-min fair allocation, dynamic programming}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2024.61
Quickly Determining Who Won an Election

Authors: Lisa Hellerstein, Naifeng Liu, and Kevin Schewior

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)

Abstract
This paper considers elections in which voters choose one candidate each, independently according to known probability distributions. A candidate receiving a strict majority (absolute or relative, depending on the version) wins. After the voters have made their choices, each vote can be inspected to determine which candidate received that vote. The time (or cost) to inspect each of the votes is known in advance. The task is to (possibly adaptively) determine the order in which to inspect the votes, so as to minimize the expected time to determine which candidate has won the election. We design polynomial-time constant-factor approximation algorithms for both the absolute-majority and the relative-majority version. Both algorithms are based on a two-phase approach. In the first phase, the algorithms reduce the number of relevant candidates to O(1), and in the second phase they utilize techniques from the literature on stochastic function evaluation to handle the remaining candidates. In the case of absolute majority, we show that the same can be achieved with only two rounds of adaptivity.
Cite as

Lisa Hellerstein, Naifeng Liu, and Kevin Schewior. Quickly Determining Who Won an Election. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 61:1-61:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@InProceedings{hellerstein_et_al:LIPIcs.ITCS.2024.61,
  author =	{Hellerstein, Lisa and Liu, Naifeng and Schewior, Kevin},
  title =	{{Quickly Determining Who Won an Election}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{61:1--61:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.61},
  URN =		{urn:nbn:de:0030-drops-195890},
  doi =		{10.4230/LIPIcs.ITCS.2024.61},
  annote =	{Keywords: stochastic function evaluation, voting, approximation algorithms}
}
Document
DOI: 10.4230/LIPIcs.ESA.2023.54
Improved Approximation Algorithms for the Expanding Search Problem

Authors: Svenja M. Griesbach, Felix Hommelsheim, Max Klimm, and Kevin Schewior

Published in: LIPIcs, Volume 274, 31st Annual European Symposium on Algorithms (ESA 2023)

Abstract
A searcher faces a graph with edge lengths and vertex weights, initially having explored only a given starting vertex. In each step, the searcher adds an edge to the solution that connects an unexplored vertex to an explored vertex. This requires an amount of time equal to the edge length. The goal is to minimize the weighted sum of the exploration times over all vertices. We show that this problem is hard to approximate and provide algorithms with improved approximation guarantees. For the general case, we give a (2e+ε)-approximation for any ε > 0. For the case that all vertices have unit weight, we provide a 2e-approximation. Finally, we provide a PTAS for the case of a Euclidean graph. Previously, for all cases only an 8-approximation was known.
Cite as

Svenja M. Griesbach, Felix Hommelsheim, Max Klimm, and Kevin Schewior. Improved Approximation Algorithms for the Expanding Search Problem. In 31st Annual European Symposium on Algorithms (ESA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 274, pp. 54:1-54:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{griesbach_et_al:LIPIcs.ESA.2023.54,
  author =	{Griesbach, Svenja M. and Hommelsheim, Felix and Klimm, Max and Schewior, Kevin},
  title =	{{Improved Approximation Algorithms for the Expanding Search Problem}},
  booktitle =	{31st Annual European Symposium on Algorithms (ESA 2023)},
  pages =	{54:1--54:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-295-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{274},
  editor =	{G{\o}rtz, Inge Li and Farach-Colton, Martin and Puglisi, Simon J. 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.2023.54},
  URN =		{urn:nbn:de:0030-drops-187073},
  doi =		{10.4230/LIPIcs.ESA.2023.54},
  annote =	{Keywords: Approximation Algorithm, Expanding Search, Search Problem, Graph Exploration, Traveling Repairperson Problem}
}
Document
DOI: 10.4230/LIPIcs.ESA.2023.62
Threshold Testing and Semi-Online Prophet Inequalities

Authors: Martin Hoefer and Kevin Schewior

Published in: LIPIcs, Volume 274, 31st Annual European Symposium on Algorithms (ESA 2023)

Abstract
We study threshold testing, an elementary probing model with the goal to choose a large value out of n i.i.d. random variables. An algorithm can test each variable X_i once for some threshold t_i, and the test returns binary feedback whether X_i ≥ t_i or not. Thresholds can be chosen adaptively or non-adaptively by the algorithm. Given the results for the tests of each variable, we then select the variable with highest conditional expectation. We compare the expected value obtained by the testing algorithm with expected maximum of the variables. Threshold testing is a semi-online variant of the gambler’s problem and prophet inequalities. Indeed, the optimal performance of non-adaptive algorithms for threshold testing is governed by the standard i.i.d. prophet inequality of approximately 0.745 + o(1) as n → ∞. We show how adaptive algorithms can significantly improve upon this ratio. Our adaptive testing strategy guarantees a competitive ratio of at least 0.869 - o(1). Moreover, we show that there are distributions that admit only a constant ratio c < 1, even when n → ∞. Finally, when each box can be tested multiple times (with n tests in total), we design an algorithm that achieves a ratio of 1 - o(1).
Cite as

Martin Hoefer and Kevin Schewior. Threshold Testing and Semi-Online Prophet Inequalities. In 31st Annual European Symposium on Algorithms (ESA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 274, pp. 62:1-62:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{hoefer_et_al:LIPIcs.ESA.2023.62,
  author =	{Hoefer, Martin and Schewior, Kevin},
  title =	{{Threshold Testing and Semi-Online Prophet Inequalities}},
  booktitle =	{31st Annual European Symposium on Algorithms (ESA 2023)},
  pages =	{62:1--62:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-295-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{274},
  editor =	{G{\o}rtz, Inge Li and Farach-Colton, Martin and Puglisi, Simon J. 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.2023.62},
  URN =		{urn:nbn:de:0030-drops-187159},
  doi =		{10.4230/LIPIcs.ESA.2023.62},
  annote =	{Keywords: Prophet Inequalities, Testing, Stochastic Probing}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2023.47
Incremental Maximization via Continuization

Authors: Yann Disser, Max Klimm, Kevin Schewior, and David Weckbecker

Published in: LIPIcs, Volume 261, 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)

Abstract
We consider the problem of finding an incremental solution to a cardinality-constrained maximization problem that not only captures the solution for a fixed cardinality, but also describes how to gradually grow the solution as the cardinality bound increases. The goal is to find an incremental solution that guarantees a good competitive ratio against the optimum solution for all cardinalities simultaneously. The central challenge is to characterize maximization problems where this is possible, and to determine the best-possible competitive ratio that can be attained. A lower bound of 2.18 and an upper bound of φ + 1 ≈ 2.618 are known on the competitive ratio for monotone and accountable objectives [Bernstein et al., Math. Prog., 2022], which capture a wide range of maximization problems. We introduce a continuization technique and identify an optimal incremental algorithm that provides strong evidence that φ + 1 is the best-possible competitive ratio. Using this continuization, we obtain an improved lower bound of 2.246 by studying a particular recurrence relation whose characteristic polynomial has complex roots exactly beyond the lower bound. Based on the optimal continuous algorithm combined with a scaling approach, we also provide a 1.772-competitive randomized algorithm. We complement this by a randomized lower bound of 1.447 via Yao’s principle.
Cite as

Yann Disser, Max Klimm, Kevin Schewior, and David Weckbecker. Incremental Maximization via Continuization. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 47:1-47:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{disser_et_al:LIPIcs.ICALP.2023.47,
  author =	{Disser, Yann and Klimm, Max and Schewior, Kevin and Weckbecker, David},
  title =	{{Incremental Maximization via Continuization}},
  booktitle =	{50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)},
  pages =	{47:1--47:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-278-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{261},
  editor =	{Etessami, Kousha and Feige, Uriel and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2023.47},
  URN =		{urn:nbn:de:0030-drops-180992},
  doi =		{10.4230/LIPIcs.ICALP.2023.47},
  annote =	{Keywords: incremental optimization, competitive analysis, robust matching, submodular function}
}
Document
Extended Abstract
DOI: 10.4230/LIPIcs.ITCS.2021.86
Unknown I.I.D. Prophets: Better Bounds, Streaming Algorithms, and a New Impossibility (Extended Abstract)

Authors: José Correa, Paul Dütting, Felix Fischer, Kevin Schewior, and Bruno Ziliotto

Published in: LIPIcs, Volume 185, 12th Innovations in Theoretical Computer Science Conference (ITCS 2021)

Abstract
A prophet inequality states, for some α ∈ [0,1], that the expected value achievable by a gambler who sequentially observes random variables X_1,… ,X_n and selects one of them is at least an α fraction of the maximum value in the sequence. We obtain three distinct improvements for a setting that was first studied by Correa et al. (EC, 2019) and is particularly relevant to modern applications in algorithmic pricing. In this setting, the random variables are i.i.d. from an unknown distribution and the gambler has access to an additional β n samples for some β ≥ 0. We first give improved lower bounds on α for a wide range of values of β; specifically, α ≥ (1+β)/e when β ≤ 1/(e-1), which is tight, and α ≥ 0.648 when β = 1, which improves on a bound of around 0.635 due to Correa et al. (SODA, 2020). Adding to their practical appeal, specifically in the context of algorithmic pricing, we then show that the new bounds can be obtained even in a streaming model of computation and thus in situations where the use of relevant data is complicated by the sheer amount of data available. We finally establish that the upper bound of 1/e for the case without samples is robust to additional information about the distribution, and applies also to sequences of i.i.d. random variables whose distribution is itself drawn, according to a known distribution, from a finite set of known candidate distributions. This implies a tight prophet inequality for exchangeable sequences of random variables, answering a question of Hill and Kertz (Contemporary Mathematics, 1992), but leaves open the possibility of better guarantees when the number of candidate distributions is small, a setting we believe is of strong interest to applications.
Cite as

José Correa, Paul Dütting, Felix Fischer, Kevin Schewior, and Bruno Ziliotto. Unknown I.I.D. Prophets: Better Bounds, Streaming Algorithms, and a New Impossibility (Extended Abstract). In 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 185, p. 86:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@InProceedings{correa_et_al:LIPIcs.ITCS.2021.86,
  author =	{Correa, Jos\'{e} and D\"{u}tting, Paul and Fischer, Felix and Schewior, Kevin and Ziliotto, Bruno},
  title =	{{Unknown I.I.D. Prophets: Better Bounds, Streaming Algorithms, and a New Impossibility}},
  booktitle =	{12th Innovations in Theoretical Computer Science Conference (ITCS 2021)},
  pages =	{86:1--86:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-177-1},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{185},
  editor =	{Lee, James R.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2021.86},
  URN =		{urn:nbn:de:0030-drops-136255},
  doi =		{10.4230/LIPIcs.ITCS.2021.86},
  annote =	{Keywords: Prophet Inequalities, Stopping Theory, Unknown Distributions}
}
  • Refine by Type
  • 20 Document/PDF
  • 8 Document/HTML

  • Refine by Publication Year
  • 9 2025
  • 2 2024
  • 3 2023
  • 1 2021
  • 1 2020
  • Show More...

  • Refine by Author
  • 14 Schewior, Kevin
  • 3 Disser, Yann
  • 2 Eberle, Franziska
  • 2 Hellerstein, Lisa
  • 2 Hoefer, Martin
  • Show More...

  • Refine by Series/Journal
  • 19 LIPIcs
  • 1 DagRep

  • Refine by Classification
  • 10 Theory of computation → Online algorithms
  • 6 Theory of computation → Approximation algorithms analysis
  • 3 Mathematics of computing → Combinatorial optimization
  • 2 Mathematics of computing → Combinatorial algorithms
  • 2 Theory of computation → Scheduling algorithms
  • Show More...

  • Refine by Keyword
  • 4 competitive analysis
  • 3 approximation algorithms
  • 3 online algorithms
  • 2 Prophet Inequalities
  • 2 adaptivity
  • Show More...

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
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact