@InProceedings{cornelilatoucheetal2015exact-icl,
  author = 	 {Corneli, Marco and Latouche, Pierre and Rossi, Fabrice},
  title = 	 {Exact ICL maximization in a non-stationary time extension of the latent block model for dynamic networks},
  abstract= {{The latent block model (LBM) is a flexible probabilistic tool to describe 
interactions between node sets in bipartite networks, but it does not
account for interactions of time varying intensity between nodes in unknown 
classes. In this paper we propose a non stationary temporal extension of the 
LBM that clusters simultaneously the two node sets of 
a bipartite network and constructs classes of time intervals on which interactions are stationary. 
The number of clusters as well as the membership to classes are obtained
by maximizing the exact complete-data integrated likelihood relying on a greedy
search approach. Experiments on simulated and real data 
are carried out in order to assess the proposed methodology.
 }},
  booktitle = {Proceedings of the 23-th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2015)},
    address = {Bruges, Belgique},
    language = {english},
    audience = {international},
  year = 	 {2015},
  pages = 	 {225--230},
  month = 	 {4},
    hal= {hal-01163367},
    arxiv={1506.04138},
    publisherlink = {http://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2015-106.pdf},
    entrysubtype={inproceedings-international-conference},
}