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This paper studies semi-supervised object classification in relational data, which is a fundamental problem in relational data modeling.
Statistical analysis of non-lattice data
Besag, J · 1975
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Probabilistic frame-based systems
Koller, D. and Pfeffer, A · 1998
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Neal, R. M. and Hinton, G. E · 1998
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Friedman, N., Getoor, L., Koller, D., and Pfeffer, A · 1999
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Zhu, X., Ghahramani, Z., and Lafferty, J. D · 2003
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Link prediction in relational data
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Learning with local and global consistency
Zhou, D., Bousquet, O., Lal, T. N., Weston, J., and Schölkopf, B · 2004
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Kok, S. and Domingos, P · 2005
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Discriminative training of markov logic networks
Singla, P. and Domingos, P · 2005
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Markov logic networks
Richardson, M. and Domingos, P · 2006
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Relational markov networks
Taskar, B., Abbeel, P., Wong, M.-F., and Koller, D · 2007
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Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K., Evans, C., Paritosh, P., Sturge, T., and Taylor, J · 2008
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Collective classification in network data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Galligher, B., and Eliassi-Rad, T · 2008
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Pseudolikelihood em for within-network relational learning
Xiang, R. and Neville, J · 2008
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Probabilistic graphical models: principles and techniques
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Rectified linear units improve restricted boltzmann machines
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node2vec: Scalable feature learning for networks
Grover, A. and Leskovec, J · 2016
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Edge weight prediction in weighted signed networks
Kumar, S., Spezzano, F., Subrahmanian, V., and Faloutsos, C · 2016
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Revisiting semi-supervised learning with graph embeddings
Yang, Z., Cohen, W., and Salakhudinov, R · 2016
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Neural message passing for quantum chemistry
Gilmer, J., Schoenholz, S. S., Riley, P. F., Vinyals, O., and Dahl, G. E · 2017
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Inductive representation learning on large graphs
Hamilton, W., Ying, Z., and Leskovec, J · 2017
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