Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

• 1J. Niehren, J. Champavère, R. Gilleron, A. Lemay.
  
  Query Induction with Schema-Guided Pruning Strategies, in: Journal of Machine Learning Research, April 2013, vol. 14, pp. 927–964.
  
  http://hal.inria.fr/inria-00607121

International Conferences with Proceedings

• 2V. Antoine, N. Asher, P. Muller, P. Denis, S. Afantenos.
  
  Expressivity and comparison of models of discourse structure, in: Special Interest Group on Discourse and Dialogue, Metz, France, August 2013.
  
  http://hal.inria.fr/hal-00838260
• 3E. Lassalle, P. Denis.
  
  Improving pairwise coreference models through feature space hierarchy learning, in: ACL 2013 - Annual meeting of the Association for Computational Linguistics, Sofia, Bulgaria, Association for Computational Linguistics, 2013.
  
  http://hal.inria.fr/hal-00838192
• 4G. Laurence, A. Lemay, J. Niehren, S. Staworko, M. Tommasi.
  
  Learning Sequential Tree-to-Word Transducers, in: 8th International Conference on Language and Automata Theory and Applications, Madrid, Spain, Springer, March 2014.
  
  http://hal.inria.fr/hal-00912969
• 5T. Ricatte, G. Garriga, R. Gilleron, M. Tommasi.
  
  Learning from Multiple Graphs using a Sigmoid Kernel, in: The 12th International Conference on Machine Learning and Applications (ICMLA'13), Miami, United States, December 2013.
  
  http://hal.inria.fr/hal-00913237

National Conferences with Proceedings

• 6C. Braud, P. Denis.
  
  Identification automatique des relations discursives "implicites" à partir de données annotées et de corpus bruts, in: TALN - 20ème conférence du Traitement Automatique du Langage Naturel 2013, Sables d'Olonne, France, June 2013, vol. 1, pp. 104-117.
  
  http://hal.inria.fr/hal-00830983
• 7E. Lassalle, P. Denis.
  
  Apprentissage d'une hiérarchie de modèles à paires spécialisés pour la résolution de la coréférence, in: TALN 2013 - 20ème conférence du Traitement Automatique du Langage Naturel 2013, Les Sables-d'Olonne, France, June 2013.
  
  http://hal.inria.fr/hal-00825617

Internal Reports

• 8T. Ricatte, G. Garriga, R. Gilleron, M. Tommasi.
  
  A Spectral Framework for a Class of Undirected Hypergraphs, December 2013.
  
  http://hal.inria.fr/hal-00914286

Other Publications

• 9A. Freno, M. Keller, M. Tommasi.
  
  Probability Estimation over Large-Scale Random Networks via the Fiedler Delta Statistic, December 2013.
  
  http://hal.inria.fr/hal-00922432

References in notes

• 10A. Alexandrescu, K. Kirchhoff.
  
  Graph-based learning for phonetic classification, in: IEEE Workshop on Automatic Speech Recognition & Understanding, ASRU 2007, Kyoto, Japan, December 9-13, 2007, 2007, pp. 359-364.
• 11M.-F. Balcan, A. Blum, P. P. Choi, J. Lafferty, B. Pantano, M. R. Rwebangira, X. Zhu.
  
  Person Identification in Webcam Images: An Application of Semi-Supervised Learning, in: ICML2005 Workshop on Learning with Partially Classified Training Data, 2005.
• 12M. Belkin, P. Niyogi.
  
  Towards a Theoretical Foundation for Laplacian-Based Manifold Methods, 2008, vol. 74, n^o 8, pp. 1289-1308.
• 13A. Bellet, A. Habrard, M. Sebban.
  
  A Survey on Metric Learning for Feature Vectors and Structured Data, in: CoRR, 2013, vol. abs/1306.6709.
• 14P. J. Bickel, A. Chen.
  
  A nonparametric view of network models and Newman–Girvan and other modularities, in: Proceedings of the National Academy of Sciences, 2009, vol. 106, pp. 21068–21073.
• 15P. Blau.
  
  Inequality and Heterogeneity: A Primitive Theory of Social Structure, MACMILLAN Company, 1977.
  
  http://books.google.fr/books?id=jvq2AAAAIAAJ
• 16N. Cesa-Bianchi, C. Gentile, F. Vitale, G. Zappella.
  
  A Linear Time Active Learning Algorithm for Link Classification, in: Proc of NIPS, 2012, pp. 1619-1627.
• 17H. Chang, D.-Y. Yeung.
  
  Graph Laplacian Kernels for Object Classification from a Single Example, in: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2, Washington, DC, USA, CVPR '06, IEEE Computer Society, 2006, pp. 2011–2016.
  
  http://dx.doi.org/10.1109/CVPR.2006.128
• 18D. Das, S. Petrov.
  
  Unsupervised Part-of-Speech Tagging with Bilingual Graph-Based Projections, in: ACL, 2011, pp. 600-609.
• 19E. R. Fernandes, U. Brefeld.
  
  Learning from Partially Annotated Sequences, in: ECML/PKDD, 2011, pp. 407-422.
• 20A. Freno, G. C. Garriga, M. Keller.
  
  Learning to Recommend Links Using Graph Structure and Node Content, in: NIPS Workshop on Choice Models and Preference Learning, 2011.
• 21A. Freno, M. Keller, C. Garriga, M. Tommasi.
  
  Spectral Estimation of Conditional Random Graph Models for Large-Scale Network data, in: Proc. of UAI 2012, Avalon, États-Unis, 2012.
  
  http://hal.inria.fr/hal-00714446
• 22A. B. Goldberg, X. Zhu.
  
  Seeing stars when there aren't many stars: graph-based semi-supervised learning for sentiment categorization, in: Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing, Stroudsburg, PA, USA, TextGraphs-1, Association for Computational Linguistics, 2006, pp. 45–52.
  
  http://dl.acm.org/citation.cfm?id=1654758.1654769
• 23A. Goldenberg, A. X. Zheng, S. E. Fienberg.
  
  A Survey of Statistical Network Models, Foundations and trends in machine learning, Now Publishers, 2010.
  
  http://books.google.fr/books?id=gPGgcOf95moC
• 24M. Gomez-Rodriguez, J. Leskovec, A. Krause.
  
  Inferring networks of diffusion and influence, in: Proc. of KDD, 2010, pp. 1019-1028.
• 25M. Herbster, S. Pasteris, F. Vitale.
  
  Online Sum-Product Computation Over Trees, in: Proc. of NIPS, 2012, pp. 2879-2887.
• 26Y. Liu, K. Kirchhoff.
  
  Graph-Based Semi-Supervised Learning for Phone and Segment Classification, in: Proceedings of Interspeech, Lyon, France, 2013.
• 27M. McPherson, L. S. Lovin, J. M. Cook.
  
  Birds of a Feather: Homophily in Social Networks, in: Annual Review of Sociology, 2001, vol. 27, n^o 1, pp. 415–444.
  
  http://dx.doi.org/10.1146/annurev.soc.27.1.415
• 28A. Nenkova, K. McKeown.
  
  A Survey of Text Summarization Techniques, in: Mining Text Data, 2012, pp. 43-76.
• 29H. Shin, K. Tsuda, B. Schölkopf.
  
  Protein functional class prediction with a combined graph, in: Expert Syst. Appl., March 2009, vol. 36, n^o 2, pp. 3284–3292.
  
  http://dx.doi.org/10.1016/j.eswa.2008.01.006
• 30S. Singh, A. Subramanya, F. C. N. Pereira, A. McCallum.
  
  Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models, in: ACL, 2011, pp. 793-803.
• 31M. Speriosu, N. Sudan, S. Upadhyay, J. Baldridge.
  
  Twitter Polarity Classification with Label Propagation over Lexical Links and the Follower Graph, in: Proceedings of the First Workshop on Unsupervised Methods in NLP, Edinburgh, Scotland, 2011.
• 32A. Subramanya, S. Petrov, F. C. N. Pereira.
  
  Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models, in: EMNLP, 2010, pp. 167-176.
• 33F. Vitale, N. Cesa-Bianchi, C. Gentile, G. Zappella.
  
  See the Tree Through the Lines: The Shazoo Algorithm, in: Proc of NIPS, 2011, pp. 1584-1592.
• 34L. Wang, S. N. Kim, T. Baldwin.
  
  The Utility of Discourse Structure in Identifying Resolved Threads in Technical User Forums, in: COLING, 2012, pp. 2739-2756.
• 35X. Zhu, Z. Ghahramani, J. D. Lafferty.
  
  Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions, in: Proc. of ICML, 2003, pp. 912-919.