8 Search Results for "Li, Ang"

Document
DOI: 10.4230/LIPIcs.ESA.2025.111
Hardness of Median and Center in the Ulam Metric

Authors: Nick Fischer, Elazar Goldenberg, Mursalin Habib, and Karthik C. S.

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

Abstract
The classical rank aggregation problem seeks to combine a set X of n permutations into a single representative "consensus" permutation. In this paper, we investigate two fundamental rank aggregation tasks under the well-studied Ulam metric: computing a median permutation (which minimizes the sum of Ulam distances to X) and computing a center permutation (which minimizes the maximum Ulam distance to X) in two settings. - Continuous Setting: In the continuous setting, the median/center is allowed to be any permutation. It is known that computing a center in the Ulam metric is NP-hard and we add to this by showing that computing a median is NP-hard as well via a simple reduction from the Max-Cut problem. While this result may not be unexpected, it had remained elusive until now and confirms a speculation by Chakraborty, Das, and Krauthgamer [SODA '21]. - Discrete Setting: In the discrete setting, the median/center must be a permutation from the input set. We fully resolve the fine-grained complexity of the discrete median and discrete center problems under the Ulam metric, proving that the naive Õ(n² L)-time algorithm (where L is the length of the permutation) is conditionally optimal. This resolves an open problem raised by Abboud, Bateni, Cohen-Addad, Karthik C. S., and Seddighin [APPROX '23]. Our reductions are inspired by the known fine-grained lower bounds for similarity measures, but we face and overcome several new highly technical challenges.
Cite as

Nick Fischer, Elazar Goldenberg, Mursalin Habib, and Karthik C. S.. Hardness of Median and Center in the Ulam Metric. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 111:1-111:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{fischer_et_al:LIPIcs.ESA.2025.111,
  author =	{Fischer, Nick and Goldenberg, Elazar and Habib, Mursalin and Karthik C. S.},
  title =	{{Hardness of Median and Center in the Ulam Metric}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{111:1--111:17},
  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.2025.111},
  URN =		{urn:nbn:de:0030-drops-245809},
  doi =		{10.4230/LIPIcs.ESA.2025.111},
  annote =	{Keywords: Ulam distance, median, center, rank aggregation, fine-grained complexity}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.7
A Modularity-Driven Framework for Unraveling Congestion Centers with Enhanced Spatial-Semantic Features

Authors: Weihua Huan, Xintao Liu, and Wei Huang

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

Abstract
The propagation of traffic congestion is a complicated spatiotemporal phenomenon in urban networks. Extensive studies mainly relied on dynamic Bayesian network or deep learning approaches. However, they often struggle to adapt seamlessly to diverse data granularities, limiting their applicability. In this study, we propose a modularity-driven method to unravel the spatiotemporal congestion propagation centers, effectively addressing temporal granularity challenges through the use of the fast Fourier Transform (FFT). Our framework distinguishes itself due to its capacity to integrate enhanced spatial-semantic features while eliminating temporal granularity dependence, which consists of two data-driven modules. One is adaptive adjacency matrix learning module, which captures the spatiotemporal relationship from evolving congestion graphs by fusing node degree, spatial proximity, and the FFT of traffic state indices. The other one is local search module, which employs local dominance principles to unravel the congestion propagation centers. We validate our proposed methodology on the large-scale traffic networks in New York City, the United States. An ablation study on the dataset reveals that the combination of the three features achieves the highest modularity scores of 0.65. The contribution of our work is to provide a novel way to infer the propagation centers of traffic congestion, and reveals the flexibility of extending our framework at temporal scales. The network resilience and dynamic evolution of the identified congestion centers can provide implications for actional decisions.
Cite as

Weihua Huan, Xintao Liu, and Wei Huang. A Modularity-Driven Framework for Unraveling Congestion Centers with Enhanced Spatial-Semantic Features. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 7:1-7:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{huan_et_al:LIPIcs.GIScience.2025.7,
  author =	{Huan, Weihua and Liu, Xintao and Huang, Wei},
  title =	{{A Modularity-Driven Framework for Unraveling Congestion Centers with Enhanced Spatial-Semantic Features}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{7:1--7:11},
  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.2025.7},
  URN =		{urn:nbn:de:0030-drops-238362},
  doi =		{10.4230/LIPIcs.GIScience.2025.7},
  annote =	{Keywords: Congestion center, Temporal granularity, Fast Fourier Transform, Local dominance}
}
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)

Copy BibTex To Clipboard

@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.WABI.2025.12
Extension of Partial Atom-To-Atom Maps: Uniqueness and Algorithms

Authors: Marcos E. González Laffitte, Tieu-Long Phan, and Peter F. Stadler

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

Abstract
Chemical reaction databases typically report the molecular structures of reactant and product compounds, as well as their stoichiometry, but lack information, in particular, on the correspondence of reactant and product atoms. These atom-to-atom maps (AAM), however, are crucial for applications including chemical synthesis planning in organic chemistry and the analysis of isotope labeling experiments in modern metabolomics. AAMs therefore need to be reconstructed computationally. This situation is aggravated, furthermore, by the fact that chemically correct AAMs are, fundamentally, determined by quantum-mechanical phenomena and thus cannot be reliably computed by solving graph-theoretical optimization problems defined by the reactant and product structures. A viable solution for this problem is to shift the focus into first identifying a partial AAM containing the reaction center, i.e., covering the atoms incident with all bonds that change during a reaction. This then leads to the problem of extending the partial map to the full reaction. The AAM of a reaction is faithfully represented by the Imaginary Transition State (ITS) graph, providing a convenient graph-theoretic framework to address the questions of when and how a partial AAM can be extended. We show that an unique extension exists whenever, and only if, these partial AAMs cover the reaction center. In this case their extension can be computed by solving a constrained graph-isomorphism search between specific subgraphs of ITS graphs. We close by benchmarking different tools for this task.
Cite as

Marcos E. González Laffitte, Tieu-Long Phan, and Peter F. Stadler. Extension of Partial Atom-To-Atom Maps: Uniqueness and Algorithms. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 12:1-12:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{gonzalezlaffitte_et_al:LIPIcs.WABI.2025.12,
  author =	{Gonz\'{a}lez Laffitte, Marcos E. and Phan, Tieu-Long and Stadler, Peter F.},
  title =	{{Extension of Partial Atom-To-Atom Maps: Uniqueness and Algorithms}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{12:1--12:26},
  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.2025.12},
  URN =		{urn:nbn:de:0030-drops-239410},
  doi =		{10.4230/LIPIcs.WABI.2025.12},
  annote =	{Keywords: atom-to-atom maps, imaginary transition state (ITS) graphs, condensed graph of the reaction (CGR), chemical reaction mechanisms, molecular graphs, metabolic networks, chemical synthesis planning, constrained graph isomorphism}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.16
Depth-Optimal Quantum Layout Synthesis as SAT

Authors: Anna B. Jakobsen, Anders B. Clausen, Jaco van de Pol, and Irfansha Shaik

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
Quantum circuits consist of gates applied to qubits. Current quantum hardware platforms impose connectivity restrictions on binary CX gates. Hence, Layout Synthesis is an important step to transpile quantum circuits before they can be executed. Since CX gates are noisy, it is important to reduce the CX count or CX depth of the mapped circuits. We provide a new and efficient encoding of Quantum-circuit Layout Synthesis in SAT. Previous SAT encodings focused on gate count and CX-gate count. Our encoding instead guarantees that we find mapped circuits with minimal circuit depth or minimal CX-gate depth. We use incremental SAT solving and parallel plans for an efficient encoding. This results in speedups of more than 10-100x compared to OLSQ2, which guarantees depth-optimality. But minimizing depth still takes more time than minimizing gate count with Q-Synth. We correlate the noise reduction achieved by simulating circuits after (CX)-count and (CX)-depth reduction. We find that minimizing for CX-count correlates better with reducing noise than minimizing for CX-depth. However, taking into account both CX-count and CX-depth provides the best noise reduction.
Cite as

Anna B. Jakobsen, Anders B. Clausen, Jaco van de Pol, and Irfansha Shaik. Depth-Optimal Quantum Layout Synthesis as SAT. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 16:1-16:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{jakobsen_et_al:LIPIcs.SAT.2025.16,
  author =	{Jakobsen, Anna B. and Clausen, Anders B. and van de Pol, Jaco and Shaik, Irfansha},
  title =	{{Depth-Optimal Quantum Layout Synthesis as SAT}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{16:1--16:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.16},
  URN =		{urn:nbn:de:0030-drops-237501},
  doi =		{10.4230/LIPIcs.SAT.2025.16},
  annote =	{Keywords: Quantum Layout Synthesis, Transpiling, Circuit Mapping, Incremental SAT, Parallel Plans}
}
Document
Resource Paper
DOI: 10.4230/TGDK.2.2.6
TØIRoads: A Road Data Model Generation Tool

Authors: Grunde Haraldsson Wesenberg and Ana Ozaki

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
We describe road data models which can represent high level features of a road network such as population, points of interest, and road length/cost and capacity, while abstracting from time and geographic location. Such abstraction allows for a simplified traffic usage and congestion analysis that focus on the high level features. We provide theoretical results regarding mass conservation and sufficient conditions for avoiding congestion within the model. We describe a road data model generation tool, which we call "TØI Roads". We also describe several parameters that can be specified by a TØI Roads user to create graph data that can serve as input for training graph neural networks (or another learning approach that receives graph data as input) for predicting congestion within the model. The road data model generation tool allows, for instance, the study of the effects of population growth and how changes in road capacity can mitigate traffic congestion.
Cite as

Grunde Haraldsson Wesenberg and Ana Ozaki. TØIRoads: A Road Data Model Generation Tool. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 6:1-6:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@Article{wesenberg_et_al:TGDK.2.2.6,
  author =	{Wesenberg, Grunde Haraldsson and Ozaki, Ana},
  title =	{{T{\O}IRoads: A Road Data Model Generation Tool}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{6:1--6:12},
  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.2.2.6},
  URN =		{urn:nbn:de:0030-drops-225901},
  doi =		{10.4230/TGDK.2.2.6},
  annote =	{Keywords: Road Data, Transportation, Graph Neural Networks, Synthetic Dataset Generation}
}
Document
DOI: 10.4230/LIPIcs.CP.2023.40
FastMapSVM for Predicting CSP Satisfiability

Authors: Kexin Zheng, Ang Li, Han Zhang, and T. K. Satish Kumar

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
Recognizing the satisfiability of Constraint Satisfaction Problems (CSPs) is NP-hard. Although several Machine Learning (ML) approaches have attempted this task by casting it as a binary classification problem, they have had only limited success for a variety of challenging reasons. First, the NP-hardness of the task does not make it amenable to straightforward approaches. Second, CSPs come in various forms and sizes while many ML algorithms impose the same form and size on their training and test instances. Third, the representation of a CSP instance is not unique since the variables and their domain values are unordered. In this paper, we propose FastMapSVM, a recently developed ML framework that leverages a distance function between pairs of objects. We define a novel distance function between two CSP instances using maxflow computations. This distance function is well defined for CSPs of different sizes. It is also invariant to the ordering on the variables and their domain values. Therefore, our framework has broader applicability compared to other approaches. We discuss various representational and combinatorial advantages of FastMapSVM. Through experiments, we also show that it outperforms other state-of-the-art ML approaches.
Cite as

Kexin Zheng, Ang Li, Han Zhang, and T. K. Satish Kumar. FastMapSVM for Predicting CSP Satisfiability. In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 40:1-40:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{zheng_et_al:LIPIcs.CP.2023.40,
  author =	{Zheng, Kexin and Li, Ang and Zhang, Han and Kumar, T. K. Satish},
  title =	{{FastMapSVM for Predicting CSP Satisfiability}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{40:1--40:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.40},
  URN =		{urn:nbn:de:0030-drops-190775},
  doi =		{10.4230/LIPIcs.CP.2023.40},
  annote =	{Keywords: Constraint Satisfaction Problems, Machine Learning, FastMapSVM}
}
Document
Invited Talk
DOI: 10.4230/OASIcs.PARMA-DITAM.2022.1
SO(DA)^2: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk)

Authors: Antonino Tumeo, Nicolas Bohm Agostini, Serena Curzel, Ankur Limaye, Cheng Tan, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Ang Li, and Joseph Manzano

Published in: OASIcs, Volume 100, 13th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 11th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2022)

Abstract
Modern data analysis applications are complex workflows composed of algorithms with diverse behaviors. They may include digital signal processing, data filtering, reduction, compression, graph algorithms, and machine learning. Their performance is highly dependent on the volume, the velocity, and the structure of the data. They are used in many different domains (from small, embedded devices, to large-scale, high-performance computing systems) but in all cases they need to provide answers with very low latency to enable real-time decision making and autonomy. Coarse-grained reconfigurable arrays (CGRAs), i.e., architectures composed of functional units able to perform complex operations interconnected through a network-on-chip and configure the datapath to map complex kernels, are a promising platform to accelerate these applications thanks to their adaptability. They provide higher flexibility than application-specific integrated circuits (ASICs) while offering increased energy efficiency and faster reconfiguration speed with respect to field-programmable gate arrays (FPGAs). However, designing and specializing CGRAs requires significant efforts. The inherent flexibility of these devices makes the application mapping process equally important to the hardware design generation. To obtain efficient systems, approaches that simultaneously considers software and hardware optimizations are necessary. In this paper, we discuss the Software Defined Architectures for Data Analytics (SO(DA)²) toolchain, an end-to-end hardware/software codesign framework to generate custom reconfigurable architectures for data analytics applications. (SO(DA)²) is composed of a high-level compiler (SODA-OPT) and a hardware generator (OpenCGRA) and can automatically explore and generate optimal CGRA designs starting from high-level programming frameworks. SO(DA)² considers partial dynamic reconfiguration as key element of the system design. We discuss the various elements of the framework and demonstrate the flow on the case study of a partial dynamic reconfigurable CGRA design for data streaming applications.
Cite as

Antonino Tumeo, Nicolas Bohm Agostini, Serena Curzel, Ankur Limaye, Cheng Tan, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Ang Li, and Joseph Manzano. SO(DA)^2: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk). In 13th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 11th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2022). Open Access Series in Informatics (OASIcs), Volume 100, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{tumeo_et_al:OASIcs.PARMA-DITAM.2022.1,
  author =	{Tumeo, Antonino and Agostini, Nicolas Bohm and Curzel, Serena and Limaye, Ankur and Tan, Cheng and Amatya, Vinay and Minutoli, Marco and Castellana, Vito Giovanni and Li, Ang and Manzano, Joseph},
  title =	{{SO(DA)^2: End-to-end Generation of Specialized Reconfigurable Architectures}},
  booktitle =	{13th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 11th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2022)},
  pages =	{1:1--1:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-231-0},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{100},
  editor =	{Palumbo, Francesca and Bispo, Jo\~{a}o and Cherubin, Stefano},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2022.1},
  URN =		{urn:nbn:de:0030-drops-161175},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2022.1},
  annote =	{Keywords: Reconfigurable architectures, data analytics}
}
  • Refine by Type
  • 8 Document/PDF
  • 6 Document/HTML

  • Refine by Publication Year
  • 5 2025
  • 1 2024
  • 1 2023
  • 1 2022

  • Refine by Author
  • 2 Li, Ang
  • 1 Agostini, Nicolas Bohm
  • 1 Amatya, Vinay
  • 1 Castellana, Vito Giovanni
  • 1 Clausen, Anders B.
  • Show More...

  • Refine by Series/Journal
  • 6 LIPIcs
  • 1 OASIcs
  • 1 TGDK

  • Refine by Classification
  • 1 Applied computing → Bioinformatics
  • 1 Computer systems organization → Reconfigurable computing
  • 1 Computing methodologies → Machine learning
  • 1 Computing methodologies → Planning for deterministic actions
  • 1 General and reference → Evaluation
  • Show More...

  • Refine by Keyword
  • 1 Circuit Mapping
  • 1 Congestion center
  • 1 Constraint Satisfaction Problems
  • 1 Fast Fourier Transform
  • 1 FastMapSVM
  • 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