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Francois Theberge
Francois Theberge
Tutte Institute for Mathematics and Computing
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Année
Clustering via hypergraph modularity
B Kamiński, V Poulin, P Prałat, P Szufel, F Théberge
PloS one 14 (11), e0224307, 2019
592019
Almost all complete binary prefix codes have a self-synchronizing string
CF Freiling, DS Jungreis, F Théberge, K Zeger
IEEE Transactions on Information Theory 49 (9), 2219-2225, 2003
352003
Artificial benchmark for community detection (ABCD)—fast random graph model with community structure
B Kamiński, P Prałat, F Théberge
Network Science 9 (2), 153-178, 2021
222021
Asymptotic estimates for blocking probabilities in a large multi-rate loss network
A Simonian, JW Roberts, F Theberge, R Mazumdar
Advances in Applied Probability 29 (3), 806-829, 1997
211997
Ensemble clustering for graphs
V Poulin, F Théberge
Complex Networks and Their Applications VII: Volume 1 Proceedings The 7th …, 2019
202019
Community detection algorithm using hypergraph modularity
B Kamiński, P Prałat, F Théberge
Complex Networks & Their Applications IX: Volume 1, Proceedings of the Ninth …, 2021
172021
Mining complex networks
B Kamiński, P Prałat, F Théberge
Chapman and Hall/CRC, 2021
162021
An unsupervised framework for comparing graph embeddings
B Kamiński, P Prałat, F Théberge
Journal of Complex Networks 8 (5), cnz043, 2020
162020
Ensemble clustering for graphs: comparisons and applications
V Poulin, F Théberge
Applied Network Science 4 (1), 51, 2019
122019
Evaluating node embeddings of complex networks
A Dehghan-Kooshkghazi, B Kamiński, Ł Kraiński, P Prałat, F Théberge
Journal of Complex Networks 10 (4), cnac030, 2022
92022
Providing QoS in large networks: Statistical multiplexing and admission control
NB Likhanov, RR Mazumdar, F Theberge
Analysis, Control and Optimization of Complex Dynamic Systems, 137-167, 2005
92005
New reduced load heuristic for computing blocking in large multirate loss networks
F Theberge, RR Mazumdar
IEE Proceedings-Communications 143 (4), 206-211, 1996
81996
Approximation formulae for blocking probabilities in a large Erlang loss system: a probabilistic approach
F Theberge, RR Mazumdar
Proceedings of INFOCOM'95 2, 804-809, 1995
81995
Modularity of the ABCD random graph model with community structure
B Kamiński, B Pankratz, P Prałat, F Théberge
Journal of Complex Networks 10 (6), cnac050, 2022
72022
Properties and performance of the ABCDE random graph model with community structure
B Kamiński, T Olczak, B Pankratz, P Prałat, F Théberge
Big Data Research 30, 100348, 2022
72022
Self-synchronization of Huffman codes
CF Freiling, DS Jungreis, F Théberge, K Zeger
IEEE International Symposium on Information Theory, 2003. Proceedings., 49, 2003
72003
Upper bounds for blocking probabilities in large multi‐rate loss networks
F Theberge, A Simonian, RR Mazumdar
Telecommunication Systems 9, 23-39, 1998
71998
Outliers in the ABCD random graph model with community structure (ABCD+ O)
B Kamiński, P Prałat, F Théberge
Complex Networks and Their Applications XI: Proceedings of The Eleventh …, 2023
52023
A scalable unsupervised framework for comparing graph embeddings
B Kamiński, P Prałat, F Théberge
Algorithms and Models for the Web Graph: 17th International Workshop, WAW …, 2020
52020
Comparing graph clusterings: Set partition measures vs. graph-aware measures
V Poulin, F Théberge
IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (6), 2127-2132, 2020
32020
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