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Hypergraph Co-Optimal Transport: Metric and Categorical Properties
[article]
2022
arXiv
pre-print
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First, we introduce a hypergraph distance based on the co-optimal transport framework of Redko et al. and study its theoretical properties. ...
Finally, we demonstrate the versatility of our Hypergraph Co-Optimal Transport (HyperCOT) framework through various examples. ...
This work was partially supported by NSF DMS 2107808, NSF IIS-1910733, and DOE DE-SC0021015. ...
arXiv:2112.03904v2
fatcat:3vntsro5srf5rkox6acq2jwu7m
Hypergraph Co-Optimal Transport: Metric and Categorical Properties
[article]
2021
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First, we introduce a hypergraph distance based on the co-optimal transport framework of Redko et al. and study its theoretical properties. ...
Finally, we demonstrate the versatility of our Hypergraph Co-Optimal Transport (HyperCOT) framework through various examples. ...
. • We extend the co-optimal transport framework of Redko et al. [32] to define an optimal transport-based distance between hypergraphs. ...
doi:10.48550/arxiv.2112.03904
fatcat:shzap67dcvcxtcuj5m4un2bs7m
Overlapping Community Extraction: A Link Hypergraph Partitioning Based Method
2014
2014 IEEE International Conference on Services Computing
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Third, we propose to use the hypergraph to assemble all local link structures, and employ hMETIS for hypergraph partitioning. ...
Second, based upon our prior work, we transform the problem of mining local link structures into a pattern mining problem, and thus present an efficient mining algorithm. ...
Note that the existing overlapping community detection methods were roughly categorized into four classes [4] (e.g., clique percolation, link partitioning, local expansion and optimization, and fuzzy ...
doi:10.1109/scc.2014.25
dblp:conf/IEEEscc/TaoWSCY14
fatcat:l2c5klg5zjbbtkorgwdzeec4dq
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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e.g. probability distributions, class membership scores) over hypergraphs, by means of optimal transportation. ...
Inspired by recent interests of developing machine learning and data mining algorithms on hypergraphs, we investigate in this paper the semi-supervised learning algorithm of propagating "soft labels" ( ...
transport (Villani 2003; , on graphs and hypergraphs. ...
doi:10.1609/aaai.v33i01.33013630
fatcat:udglxkl6rvbangtcxgbpvexgle
Hypergraph Discretization of the Cauchy Problem in General Relativity via Wolfram Model Evolution
[article]
2021
arXiv
pre-print
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(both rotating and non-rotating), and explicitly illustrate the relationship between the discrete hypergraph topology and the continuous Riemannian geometry that is being approximated. ...
The Wolfram model offers an inherently discrete formulation of the Einstein field equations as an a priori Cauchy problem, in which Cauchy initial data is specified on a single spatial hypergraph, and ...
Acknowledgments The author would like to thank Stephen Wolfram for his continual encouragement in the pursuit of the present project, as well as for useful conversations and suggestions. ...
arXiv:2102.09363v2
fatcat:6pxav3qjsne6tjee6k62dq7k5u
Neural Predicting Higher-order Patterns in Temporal Networks
2022
Proceedings of the ACM Web Conference 2022
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HIT extracts the structural representation of a node triplet of interest on the temporal hypergraph and uses it to tell what type of, when, and why the interaction expansion could happen in this triplet ...
This posts us the challenge of designing more sophisticated hypergraph models for these higher-order patterns and the associated new learning algorithms. ...
Liu and P. Li are supported by the 2021 JPMorgan Faculty Award and the National Science Foundation (NSF) award HDR-2117997. ...
doi:10.1145/3485447.3512181
fatcat:sfr6izphsbc5vaklz2ooybg37e
Neural Predicting Higher-order Patterns in Temporal Networks
[article]
2022
arXiv
pre-print
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HIT extracts the structural representation of a node triplet of interest on the temporal hypergraph and uses it to tell what type of, when, and why the interaction expansion could happen in this triplet ...
This posts us the challenge of designing more sophisticated hypergraph models for these higher-order patterns and the associated new learning algorithms. ...
Liu and P.L. are supported by the 2021 JPMorgan Faculty Award and the National Science Foundation (NSF) award HDR-2117997. ...
arXiv:2106.06039v2
fatcat:utac3kwnznc2nnwmhwhn3fess4
A Recursive Hypergraph Bipartitioning Framework for Reducing Bandwidth and Latency Costs Simultaneously
2016
IEEE Transactions on Parallel and Distributed Systems
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However, both volume-and message-related metrics should be taken into account during partitioning for a more efficient parallelization. ...
In this work, we propose a recursive hypergraph bipartitioning framework that reduces the total volume and total message count in a single phase. ...
ACKNOWLEDGMENTS This work is partially supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under project EEEAG-114E545. ...
doi:10.1109/tpds.2016.2577024
fatcat:2w5tcebcevfxrn3um4vuf6muxe
The why, how, and when of representations for complex systems
[article]
2020
arXiv
pre-print
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observed data (i.e. graphs, simplicial complexes, and hypergraphs), and relevant computational methods for each formalism. ...
At each step we consider different types of dependencies; these are properties of the system that describe how the existence of one relation among the parts of a system may influence the existence of another ...
/woman, 0% non-binary , and 19% unknown categorization. ...
arXiv:2006.02870v1
fatcat:6rp6iechmbdzdpdolgprr2vh7e
HyGNN: Drug-Drug Interaction Prediction via Hypergraph Neural Network
[article]
2022
arXiv
pre-print
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Then, we develop HyGNN consisting of a novel attention-based hypergraph edge encoder to get the representation of drugs as hyperedges and a decoder to predict the interactions between drug pairs. ...
To capture the drug similarities, we create a hypergraph from drugs' chemical substructures extracted from the SMILES strings. ...
During training, we simultaneously optimize the encoder and decoder using adam optimizer. ...
arXiv:2206.12747v3
fatcat:3ybbwvoxqfdgxiill3ztenorse
Exploring photosynthesis evolution by comparative analysis of metabolic networks between chloroplasts and photosynthetic bacteria
2006
BMC Genomics
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The properties of the entire metabolic network and the sub-network that consists of reactions directly connected to the Calvin Cycle have been analyzed using hypergraph representation. ...
network properties that are different from cyanobacteria and to analyze possible functional significance of those features. ...
Hans Bohnert, and Dr. Peter Gogarten for their insightful discussion and comments. ...
doi:10.1186/1471-2164-7-100
pmid:16646993
pmcid:PMC1524952
fatcat:syata44srvae5jvqohrgv5lyay
Challenges and Limitations of Biological Network Analysis
2022
BioTech
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Pathway and interactomics data are represented as graphs and add a new dimension of analysis, allowing, among other features, graph-based comparison of organisms' properties. ...
Finally, we discuss the challenges and the limitations of pathways and PPI network representation and analysis. ...
Hypergraphs are an extension of graphs and multigraphs. ...
doi:10.3390/biotech11030024
pmid:35892929
pmcid:PMC9326688
fatcat:7f5zp3sczzfclbbz6ty3nyremu
Automatic parallelization of a class of irregular loops for distributed memory systems
2014
ACM Transactions on Parallel Computing
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However these loops often contain data-dependent control-flow and array-access patterns. Traditional optimizations that rely on purely static analysis fail to generate parallel code in such cases. ...
We also describe algorithms to generate a parallel inspector that performs a runtime analysis of control-flow and array-access patterns, and a parallel executor to take advantage of this information. ...
Gagan Agrawal (CSE, OSU) and the reviewers for their comments and feedback with respect to existing inspector/executor techniques. We also thank Robert L. ...
doi:10.1145/2660251
fatcat:24ghpaagpzbmpgzt2bjb2wi364
Deep Graph Generators: A Survey
2021
IEEE Access
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We also present publicly available source codes, commonly used datasets, and the most widely utilized evaluation metrics. ...
Finally, we review current trends and suggest future research directions based on the existing challenges. ...
IMPLEMENTATIONS In this section, we discuss the implementation details by categorizing and summarizing commonly used datasets and evaluation metrics. ...
doi:10.1109/access.2021.3098417
fatcat:6xzg5cs75zhovdbpjkignfr3xu
Author Index
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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Optimal Pixel Labeling Algorithms for Tree Metrics
Tarsetti, Flavio
Demo: MOBIO: Mobile Biometric Face and Speaker Authentication
Taskar, Ben
Object Detection via Boundary Structure Segmentation ...
Metric-Induced Optimal Embedding for Intrinsic 3D Shape Analysis
Diffeomorphic Sulcal Shape Analysis for Cortical Surface Registration
Toledo, Ricardo
Fast and Robust Object Segmentation with the ...
doi:10.1109/cvpr.2010.5539913
fatcat:y6m5knstrzfyfin6jzusc42p54
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