22 Search Results for "Jones, Timothy"

Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.25
NEREUS: An Assistive Decision Support System for Real-Time, Adaptive Route Guidance in Extravehicular Navigation Activities on the Lunar Surface

Authors: Jasmine Q. Wu, Andrew J. Hwang, and Matthew J. Bietz

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
Extravehicular Activity (EVA) is one of the most complex operational endeavors during human lunar exploration. A key aspect of successful operations involves adapting procedures to address unexpected hazards on the lunar surface. Current route mapping systems rely heavily on static navigation planning around craters, high elevations, and extreme weather conditions to accomplish pre-defined mission objectives. However, the high-resolution data necessary for reliable route mapping is often unavailable. To address this challenge, we have designed NEREUS, a Decision Support System (DSS) that helps EVA operators on the ground respond to anomalies faster by simulating multiple alternative routes in parallel and visualizing trade-offs in consumable resources, speed, and safety as well as impact on overall mission timeline. The system offloads computationally intensive tasks like calculating the impact of evolving hazard data, allowing operators to focus on higher-level decision-making.
Cite as

Jasmine Q. Wu, Andrew J. Hwang, and Matthew J. Bietz. NEREUS: An Assistive Decision Support System for Real-Time, Adaptive Route Guidance in Extravehicular Navigation Activities on the Lunar Surface. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 25:1-25:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{wu_et_al:OASIcs.SpaceCHI.2025.25,
  author =	{Wu, Jasmine Q. and Hwang, Andrew J. and Bietz, Matthew J.},
  title =	{{NEREUS: An Assistive Decision Support System for Real-Time, Adaptive Route Guidance in Extravehicular Navigation Activities on the Lunar Surface}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{25:1--25:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.25},
  URN =		{urn:nbn:de:0030-drops-240158},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.25},
  annote =	{Keywords: Human Computer Interaction (HCI), Adaptive Navigation, Decision Support, Cognitive Load Analysis, Decision Support System, Extravehicular Activity}
}
Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.26
Movement in Low Gravity (MoLo) – LUNA: Biomechanical Modelling to Mitigate Lunar Surface Operation Risks

Authors: David Andrew Green

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
The Artemis programme seeks to develop and test concepts, hardware and approaches to support long term habitation of the Lunar surface, and future missions to Mars. In preparation for the Artemis missions determination of tasks to be performed, the functional requirements of such tasks and as mission duration extends whether physiological deconditioning becomes functionally significant, compromising the crew member’s ability to perform critical tasks on the surface, and/or upon return to earth [MoLo-LUNA – leveraging the Molo programme (and several other activities) - could become a key supporting activity for LUNA incl. validation of the Puppeteer offloading system itself via creation of a complementary MoLo-LUNA-LAB. Furthermore, the MoLo-LUNA programme could become a key facilitator of simulator suit instrumentation/definition, broader astronaut training activities and mission architecture development – including Artemis mission simulations. By employing a Puppeteer system external to the LUNA chamber hall it will optimise utilisation and cost-effectiveness of LUNA, and as such represents a critical service to future LUNA stakeholders. Furthermore, MoLo-LUNA would generate a unique data set that can be leveraged to predict de-conditioning on the Lunar surface - and thereby optimise functionality, and minimise mission risk – including informing the need for, and prescription of exercise countermeasures on the Lunar Surface and in transit. Thus, MoLo-LUNA offers a unique opportunity to place LUNA, and ESA as a key ongoing provider of evidence to define, optimise and support crew Artemis surface missions.
Cite as

David Andrew Green. Movement in Low Gravity (MoLo) – LUNA: Biomechanical Modelling to Mitigate Lunar Surface Operation Risks. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 26:1-26:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{green:OASIcs.SpaceCHI.2025.26,
  author =	{Green, David Andrew},
  title =	{{Movement in Low Gravity (MoLo) – LUNA: Biomechanical Modelling to Mitigate Lunar Surface Operation Risks}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{26:1--26:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.26},
  URN =		{urn:nbn:de:0030-drops-240166},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.26},
  annote =	{Keywords: Locomotion, hypogravity, modelling, Lunar}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2025.25
Covering a Few Submodular Constraints and Applications

Authors: Tanvi Bajpai, Chandra Chekuri, and Pooja Kulkarni

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

Abstract
We consider the problem of covering multiple submodular constraints. Given a finite ground set N, a cost function c: N → ℝ_+, r monotone submodular functions f_1,f_2,…,f_r over N and requirements b_1,b_2,…,b_r the goal is to find a minimum cost subset S ⊆ N such that f_i(S) ≥ b_i for 1 ≤ i ≤ r. When r = 1 this is the well-known Submodular Set Cover problem. Previous work [Chekuri et al., 2022] considered the setting when r is large and developed bi-criteria approximation algorithms, and approximation algorithms for the important special case when each f_i is a weighted coverage function. These are fairly general models and capture several concrete and interesting problems as special cases. The approximation ratios for these problem are at least Ω(log r) which is unavoidable when r is part of the input. In this paper, motivated by some recent applications, we consider the problem when r is a fixed constant and obtain two main results. When the f_i are weighted coverage functions from a deletion-closed set system we obtain a (1+ε)(e/(e-1))(1+β)-approximation where β is the approximation ratio for the underlying set cover instances via the natural LP. Second, for covering multiple submodular constraints we obtain a randomized bi-criteria approximation algorithm that for any given integer α ≥ 1 outputs a set S such that f_i(S) ≥ (1-1/e^α-ε)b_i for each i ∈ [r] and 𝔼[c(S)] ≤ (1+ε)α ⋅ OPT. These results show that one can obtain nearly as good an approximation for any fixed r as what one would achieve for r = 1. We also demonstrate applications of our results to implicit covering problems such as fair facility location.
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Tanvi Bajpai, Chandra Chekuri, and Pooja Kulkarni. Covering a Few Submodular Constraints and Applications. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 353, pp. 25:1-25:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bajpai_et_al:LIPIcs.APPROX/RANDOM.2025.25,
  author =	{Bajpai, Tanvi and Chekuri, Chandra and Kulkarni, Pooja},
  title =	{{Covering a Few Submodular Constraints and Applications}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)},
  pages =	{25:1--25:22},
  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.2025.25},
  URN =		{urn:nbn:de:0030-drops-243917},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2025.25},
  annote =	{Keywords: covering, linear programming, rounding, fairness}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2025.84
Algebraic Barriers to Halving Algorithmic Information Quantities in Correlated Strings

Authors: Andrei Romashchenko

Published in: LIPIcs, Volume 345, 50th International Symposium on Mathematical Foundations of Computer Science (MFCS 2025)

Abstract
We study the possibility of scaling down algorithmic information quantities in tuples of correlated strings. In particular, we address a question raised by Alexander Shen: whether, for any triple of strings (a, b, c), there exists a string z such that each conditional Kolmogorov complexity C(a|z), C(b|z), C(c|z) is approximately half of the corresponding unconditional Kolmogorov complexity. We provide a negative answer to this question by constructing a triple (a, b, c) for which no such string z exists. Our construction is based on combinatorial properties of incidences in finite projective planes and relies on recent bounds for point-line incidences over prime fields, obtained using tools from additive combinatorics and algebraic methods, notably results by Bourgain-Katz-Tao and Stevens-De Zeeuw. As an application, we show that this impossibility yields lower bounds on the communication complexity of secret key agreement protocols in certain settings. These results reveal algebraic obstructions to efficient information exchange and highlight a separation in information-theoretic behavior between fields with and without proper subfields.
Cite as

Andrei Romashchenko. Algebraic Barriers to Halving Algorithmic Information Quantities in Correlated Strings. In 50th International Symposium on Mathematical Foundations of Computer Science (MFCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 345, pp. 84:1-84:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{romashchenko:LIPIcs.MFCS.2025.84,
  author =	{Romashchenko, Andrei},
  title =	{{Algebraic Barriers to Halving Algorithmic Information Quantities in Correlated Strings}},
  booktitle =	{50th International Symposium on Mathematical Foundations of Computer Science (MFCS 2025)},
  pages =	{84:1--84:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-388-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{345},
  editor =	{Gawrychowski, Pawe{\l} and Mazowiecki, Filip and Skrzypczak, Micha{\l}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2025.84},
  URN =		{urn:nbn:de:0030-drops-241914},
  doi =		{10.4230/LIPIcs.MFCS.2025.84},
  annote =	{Keywords: Kolmogorov complexity, algorithmic information theory, communication complexity, discrete geometry}
}
Document
DOI: 10.4230/LIPIcs.DNA.31.4
Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems

Authors: Inhoo Lee, Salvador Buse, and Erik Winfree

Published in: LIPIcs, Volume 347, 31st International Conference on DNA Computing and Molecular Programming (DNA 31) (2025)

Abstract
Many molecular systems are best understood in terms of prototypical species and reactions. The central dogma and related biochemistry are rife with examples: gene i is transcribed into RNA i, which is translated into protein i; kinase n phosphorylates substrate m; protein p dimerizes with protein q. Engineered nucleic acid systems also often have this form: oligonucleotide i hybridizes to complementary oligonucleotide j; signal strand n displaces the output of seesaw gate m; hairpin p triggers the opening of target q. When there are many variants of a small number of prototypes, it can be conceptually cleaner and computationally more efficient to represent the full system in terms of indexed species (e.g. for dimerization, M_p, D_pq) and indexed reactions (M_p + M_q → D_pq). Here, we formalize the Indexed Chemical Reaction Network (ICRN) model and describe a Python software package designed to simulate such systems in the well-mixed and reaction-diffusion settings, using a differentiable programming framework originally developed for large-scale neural network models, taking advantage of GPU acceleration when available. Notably, this framework makes it straightforward to train the models’ initial conditions and rate constants to optimize a target behavior, such as matching experimental data, performing a computation, or exhibiting spatial pattern formation. The natural map of indexed chemical reaction networks onto neural network formalisms provides a tangible yet general perspective for translating concepts and techniques from the theory and practice of neural computation into the design of biomolecular systems.
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Inhoo Lee, Salvador Buse, and Erik Winfree. Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems. In 31st International Conference on DNA Computing and Molecular Programming (DNA 31). Leibniz International Proceedings in Informatics (LIPIcs), Volume 347, pp. 4:1-4:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{lee_et_al:LIPIcs.DNA.31.4,
  author =	{Lee, Inhoo and Buse, Salvador and Winfree, Erik},
  title =	{{Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems}},
  booktitle =	{31st International Conference on DNA Computing and Molecular Programming (DNA 31)},
  pages =	{4:1--4:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-399-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{347},
  editor =	{Schaeffer, Josie and Zhang, Fei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.31.4},
  URN =		{urn:nbn:de:0030-drops-238534},
  doi =		{10.4230/LIPIcs.DNA.31.4},
  annote =	{Keywords: Differentiable Programming, Chemical Reaction Networks, Reaction-Diffusion Systems}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.14
Guiding Geospatial Analysis Processes in Dealing with Modifiable Areal Unit Problems

Authors: Guoray Cai and Yue Hao

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
Geospatial analysis has been widely applied in different domains for critical decision making. However, the results of spatial analysis are often plagued with uncertainties due to measurement errors, choice of data representations, and unintended transformation artifacts. A well known example of such problems is the Modifiable Areal Unit Problem (MAUP) which has well documented effects on the outcome of spatial analysis on area-aggregated data. Existing methods for addressing the effects of MAUP are limited, are technically complex, and are often inaccessible to practitioners. As a result, analysts tend to ignore the effects of MAUP in practice due to lack of expertise, high cognitive loads, and resource limitations. To address these challenges, this paper proposes a machine-guidance approach to augment the analyst’s capacity in mitigating the effect of MAUP. Based on an analysis of practical challenges faced by human analysts, we identified multiple opportunities for the machine to guide the analysts by alerting to the rise of MAUP, assessing the impact of MAUP, choosing mitigation methods, and generating visual guidance messages using GIS functions and tools. For each of the opportunities, we characterize the behavior patterns and the underlying guidance strategies that generate the behavior. We illustrate the behavior of machine guidance using a hotspot analysis scenario in the context of crime policing, where MAUP has strong effects on the patterns of crime hotspots. Finally, we describe the computational framework used to build a prototype guidance system and identify a number of research questions to be addressed. We conclude by discussing how the machine guidance approach could be an answer to some of the toughest problems in geospatial analysis.
Cite as

Guoray Cai and Yue Hao. Guiding Geospatial Analysis Processes in Dealing with Modifiable Areal Unit Problems. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 14:1-14:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{cai_et_al:LIPIcs.GIScience.2025.14,
  author =	{Cai, Guoray and Hao, Yue},
  title =	{{Guiding Geospatial Analysis Processes in Dealing with Modifiable Areal Unit Problems}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{14:1--14:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.14},
  URN =		{urn:nbn:de:0030-drops-238433},
  doi =		{10.4230/LIPIcs.GIScience.2025.14},
  annote =	{Keywords: Machine Guidance, Geo-Spatial Analysis, Modifiable Areal Unit Problem (MAUP)}
}
Document
DOI: 10.4230/LIPIcs.WABI.2025.10
DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs

Authors: Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract
Determining the distance between two loci within a genomic region is a recurrent operation in various tasks in computational genomics. A notable example of this task arises in paired-end read mapping as a form of validation of distances between multiple alignments. While straightforward for a single genome, graph-based reference structures render the operation considerably more involved. Given the sheer number of such queries in a typical read mapping experiment, an efficient algorithm for answering distance queries is crucial. In this paper, we introduce DiVerG, a compact data structure as well as a fast and scalable algorithm, for constructing distance indexes for general sequence graphs on multi-core CPU and many-core GPU architectures. DiVerG is based on PairG [Jain et al., 2019], but overcomes the limitations of PairG by exploiting the extensive potential for improvements in terms of scalability and space efficiency. As a consequence, DiVerG can process substantially larger datasets, such as whole human genomes, which are unmanageable by PairG. DiVerG offers faster index construction time and consistently faster query time with gains proportional to the size of the underlying compact data structure. We demonstrate that our method performs favorably on multiple real datasets at various scales. DiVerG achieves superior performance over PairG; e.g. resulting to 2.5-4x speed-up in query time, 44-340x smaller index size, and 3-50x faster construction time for the genome graph of the MHC region, as a particularly variable region of the human genome. The implementation is available at: https://github.com/cartoonist/diverg
Cite as

Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall. DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 10:1-10:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ghaffaari_et_al:LIPIcs.WABI.2025.10,
  author =	{Ghaffaari, Ali and Sch\"{o}nhuth, Alexander and Marschall, Tobias},
  title =	{{DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{10:1--10:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.10},
  URN =		{urn:nbn:de:0030-drops-239369},
  doi =		{10.4230/LIPIcs.WABI.2025.10},
  annote =	{Keywords: Sequence graph, distance index, read mapping, sparse matrix}
}
Document
DOI: 10.4230/LIPIcs.WABI.2025.11
Mutational Signature Refitting on Sparse Pan-Cancer Data

Authors: Gal Gilad, Teresa M. Przytycka, and Roded Sharan

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract
Mutational processes shape cancer genomes, leaving characteristic marks that are termed signatures. The level of activity of each such process, or its signature exposure, provides important information on the disease, improving patient stratification and the prediction of drug response. Thus, there is growing interest in developing refitting methods that decipher those exposures. Previous work in this domain was unsupervised in nature, employing algebraic decomposition and probabilistic inference methods. Here we provide a supervised approach to the problem of signature refitting and show its superiority over current methods. Our method, SuRe, leverages a neural network model to capture correlations between signature exposures in real data. We show that SuRe outperforms previous methods on sparse mutation data from tumor type specific data sets, as well as pan-cancer data sets, with an increasing advantage as the data become sparser. We further demonstrate its utility in clinical settings.
Cite as

Gal Gilad, Teresa M. Przytycka, and Roded Sharan. Mutational Signature Refitting on Sparse Pan-Cancer Data. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 11:1-11:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gilad_et_al:LIPIcs.WABI.2025.11,
  author =	{Gilad, Gal and Przytycka, Teresa M. and Sharan, Roded},
  title =	{{Mutational Signature Refitting on Sparse Pan-Cancer Data}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{11:1--11:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.11},
  URN =		{urn:nbn:de:0030-drops-239374},
  doi =		{10.4230/LIPIcs.WABI.2025.11},
  annote =	{Keywords: mutational signatures, signature refitting, cancer genomics, genomic data analysis, somatic mutations}
}
Document
DOI: 10.4230/OASIcs.Manzini.7
Algorithms for Computing Very Large BWTs: a Short Survey

Authors: Diego Díaz-Domínguez, Lavinia Egidi, Veronica Guerrini, Felipe A. Louza, and Giovanna Rosone

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
The Burrows-Wheeler Transform (BWT) is a fundamental string transformation that, although initially introduced for data compression, has been extensively utilized across various domains, including text indexing and pattern matching within large datasets. Although the BWT construction is linear, the constants make the task impractical for large datasets, and as highlighted by Ferragina et al. [Paolo Ferragina et al., 2012], "to use it, one must first build it!". Thus, the construction of the BWT remains a significant challenge. For these reasons, during the past three decades there has been a succession of new algorithms for its construction using techniques that work in external memory or that use text compression. In this survey, we revise some of the most important advancements and tools presented in the past years for computing large BWTs exploiting external memory or text compression approaches without using additional information about the data.
Cite as

Diego Díaz-Domínguez, Lavinia Egidi, Veronica Guerrini, Felipe A. Louza, and Giovanna Rosone. Algorithms for Computing Very Large BWTs: a Short Survey. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 7:1-7:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{diazdominguez_et_al:OASIcs.Manzini.7,
  author =	{D{\'\i}az-Dom{\'\i}nguez, Diego and Egidi, Lavinia and Guerrini, Veronica and Louza, Felipe A. and Rosone, Giovanna},
  title =	{{Algorithms for Computing Very Large BWTs: a Short Survey}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{7:1--7:28},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.7},
  URN =		{urn:nbn:de:0030-drops-239151},
  doi =		{10.4230/OASIcs.Manzini.7},
  annote =	{Keywords: Burrows-Wheeler transform, Extended Burrows-Wheeler transform, external memory, text compression, longest common prefix}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.61
How to Compute the Volume in Low Dimension?

Authors: Arjan Cornelissen, Simon Apers, and Sander Gribling

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

Abstract
Estimating the volume of a convex body is a canonical problem in theoretical computer science. Its study has led to major advances in randomized algorithms, Markov chain theory, and computational geometry. In particular, determining the query complexity of volume estimation to a membership oracle has been a longstanding open question. Most of the previous work focuses on the high-dimensional limit. In this work, we tightly characterize the deterministic, randomized and quantum query complexity of this problem in the high-precision limit, i.e., when the dimension is constant.
Cite as

Arjan Cornelissen, Simon Apers, and Sander Gribling. How to Compute the Volume in Low Dimension?. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 61:1-61:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{cornelissen_et_al:LIPIcs.ICALP.2025.61,
  author =	{Cornelissen, Arjan and Apers, Simon and Gribling, Sander},
  title =	{{How to Compute the Volume in Low Dimension?}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{61:1--61:18},
  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.2025.61},
  URN =		{urn:nbn:de:0030-drops-234381},
  doi =		{10.4230/LIPIcs.ICALP.2025.61},
  annote =	{Keywords: Query complexity, computational geometry, quantum computing, volume estimation, high-precision limit}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.32
Faster Algorithms for Reverse Shortest Path in Unit-Disk Graphs and Related Geometric Optimization Problems: Improving the Shrink-And-Bifurcate Technique

Authors: Timothy M. Chan and Zhengcheng Huang

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

Abstract
In a series of papers, Avraham, Filtser, Kaplan, Katz, and Sharir (SoCG'14), Kaplan, Katz, Saban, and Sharir (ESA'23), and Katz, Saban, and Sharir (ESA'24) studied a class of geometric optimization problems - including reverse shortest path in unweighted and weighted unit-disk graphs, discrete Fréchet distance with one-sided shortcuts, and reverse shortest path in visibility graphs on 1.5-dimensional terrains - for which standard parametric search does not work well due to a lack of efficient parallel algorithms for the corresponding decision problems. The best currently known algorithms for all the above problems run in O^*(n^{6/5}) = O^*(n^{1.2}) time (ignoring subpolynomial factors), and they were obtained using a technique called shrink-and-bifurcate. We improve the running time to Õ(n^{8/7}) ≈ O(n^{1.143}) for these problems. Furthermore, specifically for reverse shortest path in unweighted unit-disk graphs, we improve the running time further to Õ(n^{9/8}) = Õ(n^{1.125}).
Cite as

Timothy M. Chan and Zhengcheng Huang. Faster Algorithms for Reverse Shortest Path in Unit-Disk Graphs and Related Geometric Optimization Problems: Improving the Shrink-And-Bifurcate Technique. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 32:1-32:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{chan_et_al:LIPIcs.SoCG.2025.32,
  author =	{Chan, Timothy M. and Huang, Zhengcheng},
  title =	{{Faster Algorithms for Reverse Shortest Path in Unit-Disk Graphs and Related Geometric Optimization Problems: Improving the Shrink-And-Bifurcate Technique}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{32:1--32:14},
  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.2025.32},
  URN =		{urn:nbn:de:0030-drops-231845},
  doi =		{10.4230/LIPIcs.SoCG.2025.32},
  annote =	{Keywords: Geometric optimization problems, parametric search, shortest path, disk graphs, Fr\'{e}chet distance, visibility, distance selection, randomized algorithms}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.42
Range Counting Oracles for Geometric Problems

Authors: Anne Driemel, Morteza Monemizadeh, Eunjin Oh, Frank Staals, and David P. Woodruff

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

Abstract
In this paper, we study estimators for geometric optimization problems in the sublinear geometric model. In this model, we have oracle access to a point set with size n in a discrete space [Δ]^d, where queries can be made to an oracle that responds to orthogonal range counting requests. The query complexity of an optimization problem is measured by the number of oracle queries required to compute an estimator for the problem. We investigate two problems in this framework, the Euclidean Minimum Spanning Tree (MST) and Earth Mover Distance (EMD). For EMD, we show the existence of an estimator that approximates the cost of EMD with O(log Δ)-relative error and O(nΔ/(s^{1+1/d}))-additive error using O(s polylog Δ) range counting queries for any parameter s with 1 ≤ s ≤ n. Moreover, we prove that this bound is tight. For MST, we demonstrate that the weight of MST can be estimated within a factor of (1 ± ε) using Õ(√n) range counting queries.
Cite as

Anne Driemel, Morteza Monemizadeh, Eunjin Oh, Frank Staals, and David P. Woodruff. Range Counting Oracles for Geometric Problems. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 42:1-42:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{driemel_et_al:LIPIcs.SoCG.2025.42,
  author =	{Driemel, Anne and Monemizadeh, Morteza and Oh, Eunjin and Staals, Frank and Woodruff, David P.},
  title =	{{Range Counting Oracles for Geometric Problems}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{42:1--42:16},
  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.2025.42},
  URN =		{urn:nbn:de:0030-drops-231941},
  doi =		{10.4230/LIPIcs.SoCG.2025.42},
  annote =	{Keywords: Range counting oracles, minimum spanning trees, Earth Mover’s Distance}
}
Document
DOI: 10.4230/LIPIcs.OPODIS.2024.24
Hash & Adjust: Competitive Demand-Aware Consistent Hashing

Authors: Arash Pourdamghani, Chen Avin, Robert Sama, Maryam Shiran, and Stefan Schmid

Published in: LIPIcs, Volume 324, 28th International Conference on Principles of Distributed Systems (OPODIS 2024)

Abstract
Distributed systems often serve dynamic workloads and resource demands evolve over time. Such a temporal behavior stands in contrast to the static and demand-oblivious nature of most data structures used by these systems. In this paper, we are particularly interested in consistent hashing, a fundamental building block in many large distributed systems. Our work is motivated by the hypothesis that a more adaptive approach to consistent hashing can leverage structure in the demand, and hence improve storage utilization and reduce access time. We initiate the study of demand-aware consistent hashing. Our main contribution is H&A, a constant-competitive online algorithm (i.e., it comes with provable performance guarantees over time). H&A is demand-aware and optimizes its internal structure to enable faster access times, while offering a high utilization of storage. We further evaluate H&A empirically.
Cite as

Arash Pourdamghani, Chen Avin, Robert Sama, Maryam Shiran, and Stefan Schmid. Hash & Adjust: Competitive Demand-Aware Consistent Hashing. In 28th International Conference on Principles of Distributed Systems (OPODIS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 324, pp. 24:1-24:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{pourdamghani_et_al:LIPIcs.OPODIS.2024.24,
  author =	{Pourdamghani, Arash and Avin, Chen and Sama, Robert and Shiran, Maryam and Schmid, Stefan},
  title =	{{Hash \& Adjust: Competitive Demand-Aware Consistent Hashing}},
  booktitle =	{28th International Conference on Principles of Distributed Systems (OPODIS 2024)},
  pages =	{24:1--24:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-360-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{324},
  editor =	{Bonomi, Silvia and Galletta, Letterio and Rivi\`{e}re, Etienne and Schiavoni, Valerio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2024.24},
  URN =		{urn:nbn:de:0030-drops-225607},
  doi =		{10.4230/LIPIcs.OPODIS.2024.24},
  annote =	{Keywords: Consistent hashing, demand-awareness, online algorithms}
}
Document
Resource Paper
DOI: 10.4230/TGDK.2.2.4
FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset

Authors: Sheeba Samuel and Daniel Mietchen

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2

Abstract
The way in which data are shared can affect their utility and reusability. Here, we demonstrate how data that we had previously shared in bulk can be mobilized further through a knowledge graph that allows for much more granular exploration and interrogation. The original dataset is about the computational reproducibility of GitHub-hosted Jupyter notebooks associated with biomedical publications. It contains rich metadata about the publications, associated GitHub repositories and Jupyter notebooks, and the notebooks' reproducibility. We took this dataset, converted it into semantic triples and loaded these into a triple store to create a knowledge graph - FAIR Jupyter - that we made accessible via a web service. This enables granular data exploration and analysis through queries that can be tailored to specific use cases. Such queries may provide details about any of the variables from the original dataset, highlight relationships between them or combine some of the graph’s content with materials from corresponding external resources. We provide a collection of example queries addressing a range of use cases in research and education. We also outline how sets of such queries can be used to profile specific content types, either individually or by class. We conclude by discussing how such a semantically enhanced sharing of complex datasets can both enhance their FAIRness - i.e., their findability, accessibility, interoperability, and reusability - and help identify and communicate best practices, particularly with regards to data quality, standardization, automation and reproducibility.
Cite as

Sheeba Samuel and Daniel Mietchen. FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 4:1-4:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{samuel_et_al:TGDK.2.2.4,
  author =	{Samuel, Sheeba and Mietchen, Daniel},
  title =	{{FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:24},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.4},
  URN =		{urn:nbn:de:0030-drops-225886},
  doi =		{10.4230/TGDK.2.2.4},
  annote =	{Keywords: Knowledge Graph, Computational reproducibility, Jupyter notebooks, FAIR data, PubMed Central, GitHub, Python, SPARQL}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2020.50
Fast Algorithms for Geometric Consensuses

Authors: Sariel Har-Peled and Mitchell Jones

Published in: LIPIcs, Volume 164, 36th International Symposium on Computational Geometry (SoCG 2020)

Abstract
Let P be a set of n points in ℝ^d in general position. A median hyperplane (roughly) splits the point set P in half. The yolk of P is the ball of smallest radius intersecting all median hyperplanes of P. The egg of P is the ball of smallest radius intersecting all hyperplanes which contain exactly d points of P. We present exact algorithms for computing the yolk and the egg of a point set, both running in expected time O(n^(d-1) log n). The running time of the new algorithm is a polynomial time improvement over existing algorithms. We also present algorithms for several related problems, such as computing the Tukey and center balls of a point set, among others.
Cite as

Sariel Har-Peled and Mitchell Jones. Fast Algorithms for Geometric Consensuses. In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 50:1-50:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{harpeled_et_al:LIPIcs.SoCG.2020.50,
  author =	{Har-Peled, Sariel and Jones, Mitchell},
  title =	{{Fast Algorithms for Geometric Consensuses}},
  booktitle =	{36th International Symposium on Computational Geometry (SoCG 2020)},
  pages =	{50:1--50:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-143-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{164},
  editor =	{Cabello, Sergio and Chen, Danny Z.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2020.50},
  URN =		{urn:nbn:de:0030-drops-122088},
  doi =		{10.4230/LIPIcs.SoCG.2020.50},
  annote =	{Keywords: Geometric optimization, centerpoint, voting games}
}
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