7 Search Results for "DeVito, Zachary"

Document
DOI: 10.4230/LIPIcs.SoCG.2026.32
Tensor Computation of Euler Characteristic Functions and Transforms

Authors: Jessi Cisewski-Kehe, Brittany Terese Fasy, Alexander McCleary, and Eli Quist

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)

Abstract
The weighted Euler characteristic transform (WECT) and Euler characteristic function (ECF) have proven to be useful tools in a variety of applications. However, current methods for computing these functions are either not optimized for GPU computation or do not scale to higher-dimensional settings. In this work, we present a tensor-based framework for computing such topological descriptors which is highly optimized for GPU architectures and works in full generality across simplicial and cubical complexes of arbitrary dimension. Experimentally, the framework demonstrates significant speedups over existing methods when computing the WECT and ECF across a variety of two- and three-dimensional datasets. Computation of these transforms is implemented in a publicly available Python package called pyECT.
Cite as

Jessi Cisewski-Kehe, Brittany Terese Fasy, Alexander McCleary, and Eli Quist. Tensor Computation of Euler Characteristic Functions and Transforms. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 32:1-32:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{cisewskikehe_et_al:LIPIcs.SoCG.2026.32,
  author =	{Cisewski-Kehe, Jessi and Fasy, Brittany Terese and McCleary, Alexander and Quist, Eli},
  title =	{{Tensor Computation of Euler Characteristic Functions and Transforms}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{32:1--32:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.32},
  URN =		{urn:nbn:de:0030-drops-258380},
  doi =		{10.4230/LIPIcs.SoCG.2026.32},
  annote =	{Keywords: Topological data analysis, weighted Euler characteristic transform, Euler characteristic function, tensor computation, GPU computation}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.95
Identity Testing for Circuits with Exponentiation Gates

Authors: Jiatu Li and Mengdi Wu

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
Motivated by practical applications in the design of optimization compilers for neural networks, we initiated the study of identity testing problems for arithmetic circuits augmented with exponentiation gates that compute the real function x↦ e^x. These circuits compute real functions of form P(→x)/P'(→x), where both P(→x) and P'(→x) are exponential polynomials ∑_{i = 1}^k f_i(→x)⋅ exp((g_i(→x))/(h_i(→x))), for polynomials f_i(→x),g_i(→x), and h_i(→x). We formalize a black-box query model over finite fields for this class of circuits, which is mathematical simple and reflects constraints faced by real-world neural network compilers. We proved that a simple and efficient randomized identity testing algorithm achieves perfect completeness and non-trivial soundness. Concurrent with our work, the algorithm has been implemented in the optimization compiler Mirage by Wu et al. (OSDI 2025), demonstrating promising empirical performance in both efficiency and soundness error. Finally, we propose a number-theoretic conjecture under which our algorithm is sound with high probability.
Cite as

Jiatu Li and Mengdi Wu. Identity Testing for Circuits with Exponentiation Gates. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 95:1-95:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{li_et_al:LIPIcs.ITCS.2026.95,
  author =	{Li, Jiatu and Wu, Mengdi},
  title =	{{Identity Testing for Circuits with Exponentiation Gates}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{95:1--95:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.95},
  URN =		{urn:nbn:de:0030-drops-253821},
  doi =		{10.4230/LIPIcs.ITCS.2026.95},
  annote =	{Keywords: Polynomial Identity Testing, Exponential Polynomials}
}
Document
Research
DOI: 10.4230/TGDK.3.3.4
Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web

Authors: Florian Ruosch, Cristina Sarasua, and Abraham Bernstein

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract
In Argument Mining, predicting argumentative relations between texts (or spans) remains one of the most challenging aspects, even more so in the cross-document setting. This paper makes three key contributions to advance research in this domain. We first extend an existing dataset, the Sci-Arg corpus, by annotating it with explicit inter-document argumentative relations, thereby allowing arguments to be distributed over several documents forming an Argument Web; these new annotations are published using Semantic Web technologies (RDF, OWL). Second, we explore and evaluate three automated approaches for predicting these inter-document argumentative relations, establishing critical baselines on the new dataset. We find that a simple classifier based on discourse indicators with access to context outperforms neural methods. Third, we conduct a comparative analysis of these approaches for both intra- and inter-document settings, identifying statistically significant differences in results that indicate the necessity of distinguishing between these two scenarios. Our findings highlight significant challenges in this complex domain and open crucial avenues for future research on the Argument Web of Science, particularly for those interested in leveraging Semantic Web technologies and knowledge graphs to understand scholarly discourse. With this, we provide the first stepping stones in the form of a benchmark dataset, three baseline methods, and an initial analysis for a systematic exploration of this field relevant to the Web of Data and Science.
Cite as

Florian Ruosch, Cristina Sarasua, and Abraham Bernstein. Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 4:1-4:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ruosch_et_al:TGDK.3.3.4,
  author =	{Ruosch, Florian and Sarasua, Cristina and Bernstein, Abraham},
  title =	{{Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:33},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.4},
  URN =		{urn:nbn:de:0030-drops-252159},
  doi =		{10.4230/TGDK.3.3.4},
  annote =	{Keywords: Argument Mining, Large Language Models, Knowledge Graphs, Link Prediction}
}
Document
DOI: 10.4230/LIPIcs.TIME.2025.6
GradSTL: Comprehensive Signal Temporal Logic for Neurosymbolic Reasoning and Learning

Authors: Mark Chevallier, Filip Smola, Richard Schmoetten, and Jacques D. Fleuriot

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract
We present GradSTL, the first fully comprehensive implementation of signal temporal logic (STL) suitable for integration with neurosymbolic learning. In particular, GradSTL can successfully evaluate any STL constraint over any signal, regardless of how it is sampled. Our formally verified approach specifies smooth STL semantics over tensors, with formal proofs of soundness and of correctness of its derivative function. Our implementation is generated automatically from this formalisation, without manual coding, guaranteeing correctness by construction. We show via a case study that using our implementation, a neurosymbolic process learns to satisfy a pre-specified STL constraint. Our approach offers a highly rigorous foundation for integrating signal temporal logic and learning by gradient descent.
Cite as

Mark Chevallier, Filip Smola, Richard Schmoetten, and Jacques D. Fleuriot. GradSTL: Comprehensive Signal Temporal Logic for Neurosymbolic Reasoning and Learning. In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 6:1-6:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{chevallier_et_al:LIPIcs.TIME.2025.6,
  author =	{Chevallier, Mark and Smola, Filip and Schmoetten, Richard and Fleuriot, Jacques D.},
  title =	{{GradSTL: Comprehensive Signal Temporal Logic for Neurosymbolic Reasoning and Learning}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{6:1--6:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.6},
  URN =		{urn:nbn:de:0030-drops-244528},
  doi =		{10.4230/LIPIcs.TIME.2025.6},
  annote =	{Keywords: Signal temporal logic, spatio-temporal reasoning, neurosymbolic learning}
}
Document
Extended Abstract
DOI: 10.4230/OASIcs.Programming.2025.1
Comparing R Bytecode Compilers Written in R, Java, and Rust (Extended Abstract)

Authors: Pierre Donat-Bouillud, Filip Křikava, Jakob Hain, Adam Plodek, and Jan Vitek

Published in: OASIcs, Volume 134, Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)

Abstract
This paper presents a comparative analysis of three implementations of the R bytecode compiler: the official R implementation, a Java-based compiler, and a Rust-based compiler. The R compiler, written in R itself, poses challenges in terms of performance and maintainability. We evaluate designs of the compilers, their trade-offs, and performance characteristics. The Rust version outperforms the Java version, which itself outperforms the R version.
Cite as

Pierre Donat-Bouillud, Filip Křikava, Jakob Hain, Adam Plodek, and Jan Vitek. Comparing R Bytecode Compilers Written in R, Java, and Rust (Extended Abstract). In Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025). Open Access Series in Informatics (OASIcs), Volume 134, pp. 1:1-1:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{donatbouillud_et_al:OASIcs.Programming.2025.1,
  author =	{Donat-Bouillud, Pierre and K\v{r}ikava, Filip and Hain, Jakob and Plodek, Adam and Vitek, Jan},
  title =	{{Comparing R Bytecode Compilers Written in R, Java, and Rust}},
  booktitle =	{Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)},
  pages =	{1:1--1:6},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-382-9},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{134},
  editor =	{Edwards, Jonathan and Perera, Roly and Petricek, Tomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Programming.2025.1},
  URN =		{urn:nbn:de:0030-drops-242854},
  doi =		{10.4230/OASIcs.Programming.2025.1},
  annote =	{Keywords: R, bytecode, compiler}
}
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/LIPIcs.SNAPL.2015.79
The Design of Terra: Harnessing the Best Features of High-Level and Low-Level Languages

Authors: Zachary DeVito and Pat Hanrahan

Published in: LIPIcs, Volume 32, 1st Summit on Advances in Programming Languages (SNAPL 2015)

Abstract
Applications are often written using a combination of high-level and low-level languages since it allows performance critical parts to be carefully optimized, while other parts can be written more productively. This approach is used in web development, game programming, and in build systems for applications themselves. However, most languages were not designed with interoperability in mind, resulting in glue code and duplicated features that add complexity. We propose a two-language system where both languages were designed to interoperate. Lua is used for our high-level language since it was originally designed with interoperability in mind. We create a new low-level language, Terra, that we designed to interoperate with Lua. It is embedded in Lua, and meta-programmed from it, but has a low level of abstraction suited for writing high-performance code. We discuss important design decisions - compartmentalized runtimes, glue-free interoperation, and meta-programming features - that enable Lua and Terra to be more powerful than the sum of their parts.
Cite as

Zachary DeVito and Pat Hanrahan. The Design of Terra: Harnessing the Best Features of High-Level and Low-Level Languages. In 1st Summit on Advances in Programming Languages (SNAPL 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 32, pp. 79-89, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{devito_et_al:LIPIcs.SNAPL.2015.79,
  author =	{DeVito, Zachary and Hanrahan, Pat},
  title =	{{The Design of Terra: Harnessing the Best Features of High-Level and Low-Level Languages}},
  booktitle =	{1st Summit on Advances in Programming Languages (SNAPL 2015)},
  pages =	{79--89},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-80-4},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{32},
  editor =	{Ball, Thomas and Bodík, Rastislav and Krishnamurthi, Shriram and Lerner, Benjamin S. and Morriset, Greg},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2015.79},
  URN =		{urn:nbn:de:0030-drops-50186},
  doi =		{10.4230/LIPIcs.SNAPL.2015.79},
  annote =	{Keywords: language interoperability, meta-programming, high-performance, Lua}
}
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