Vince Lyzinski
Orcid: 0000-0001-5594-8956
According to our database1,
Vince Lyzinski
authored at least 42 papers
between 2013 and 2025.
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Bibliography
2025
Lost in the shuffle: Testing power in the presence of errorful network vertex labels.
Comput. Stat. Data Anal., 2025
2024
IEEE Trans. Signal Inf. Process. over Networks, 2024
2023
Stat. Comput., April, 2023
Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference.
J. Comput. Graph. Stat., January, 2023
IEEE Trans. Netw. Sci. Eng., 2023
2022
J. Comput. Graph. Stat., October, 2022
Signed and unsigned partial information decompositions of continuous network interactions.
J. Complex Networks, August, 2022
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks.
J. Mach. Learn. Res., 2022
Adversarial contamination of networks in the setting of vertex nomination: a new trimming method.
CoRR, 2022
2021
Graph Matching Between Bipartite and Unipartite Networks: To Collapse, or Not to Collapse, That Is the Question.
IEEE Trans. Netw. Sci. Eng., 2021
J. Comput. Graph. Stat., 2021
CoRR, 2021
The phantom alignment strength conjecture: practical use of graph matching alignment strength to indicate a meaningful graph match.
Appl. Netw. Sci., 2021
2020
IEEE Trans. Pattern Anal. Mach. Intell., 2020
Vertex nomination: The canonical sampling and the extended spectral nomination schemes.
Comput. Stat. Data Anal., 2020
On the role of features in vertex nomination: Content and context together are better (sometimes).
CoRR, 2020
2019
Neural variational entity set expansion for automatically populated knowledge graphs.
Inf. Retr. J., 2019
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019
2018
IEEE Trans. Inf. Theory, 2018
2017
IEEE Trans. Signal Process., 2017
IEEE Trans. Parallel Distributed Syst., 2017
IEEE Trans. Netw. Sci. Eng., 2017
Pattern Recognit. Lett., 2017
J. Mach. Learn. Res., 2017
A Central Limit Theorem for an Omnibus Embedding of Multiple Random Dot Product Graphs.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017
2016
IEEE Trans. Pattern Anal. Mach. Intell., 2016
On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Maximum Likelihood Estimation and Graph Matching.
J. Mach. Learn. Res., 2016
Semi-External Memory Sparse Matrix Multiplication on Billion-node Graphs in a Multicore Architecture.
CoRR, 2016
2015
Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015
2014
2013