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Despite the exploding interest in graph neural networks there has been little effort to verify and improve their robustness.
Adversarial defense framework for graph neural network
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A reformulation-convexification approach for solving nonconvex quadratic programming problems
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Semidefinite programming
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Constrained Markov decision processes , volume 7
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Automating the construction of internet portals with machine learning
McCallum, A., Nigam, K., Rennie, J., and Seymore, K · 2000
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Topic-sensitive pagerank
Haveliwala, T. H · 2002
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Scaling personalized web search
Jeh, G. and Widom, J · 2003
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Learning with local and global consistency
Zhou, D., Bousquet, O., Lal, T. N., Weston, J., and Schölkopf, B · 2003
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Learning from labeled and unlabeled data on a directed graph
Zhou, D., Huang, J., and Schölkopf, B · 2005
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The effect of new links on google pagerank
Avrachenkov, K. and Litvak, N · 2006
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Spectral clustering and transductive learning with multiple views
Zhou, D. and Burges, C. J. C · 2007
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Parameterized complexity of cardinality constrained optimization problems
Cai, L · 2008
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Maximizing pagerank via outlinks
de Kerchove, C., Ninove, L., and Van Dooren, P · 2008
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Collective classification in network data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Gallagher, B., and Eliassi-Rad, T · 2008
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Adversarial web search
Castillo, C. and Davison, B. D · 2010
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Pagerank optimization in polynomial time by stochastic shortest path reformulation
Csáji, B. C., Jungers, R. M., and Blondel, V. D · 2010
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Maximizing pagerank with new backlinks
Olsen, M · 2010
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A constant-factor approximation algorithm for the link building problem
Olsen, M., Viglas, A., and Zvedeniouk, I · 2010
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Policy iteration is well suited to optimize pagerank
Hollanders, R., Delvenne, J.-C., and Jungers, R · 2011
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Optimization of Perron eigenvectors and applications: from web ranking to chronotherapeutics
Fercoq, O · 2012
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Generalized optimization framework for graph-based semi-supervised learning
Sokol, M., Avrachenkov, K., Gonçalves, P., and Mishenin, A · 2012
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Ergodic control and polyhedral approaches to pagerank optimization
Hybrid approach of relation network and localized graph convolutional filtering for breast cancer subtype classification
Rhee, S., Seo, S., and Kim, S · 2018
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Provable defenses against adversarial examples via the convex outer adversarial polytope
Wong, E. and Kolter, J. Z · 2018
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Graph convolutional neural networks for web-scale recommender systems
Ying, R., He, R., Chen, K., Eksombatchai, P., Hamilton, W. L., and Leskovec, J · 2018
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Adversarial attacks on neural networks for graph data
Zügner, D., Akbarnejad, A., and Günnemann, S · 2018
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Adversarial attacks on node embeddings via graph poisoning
Bojchevski, A. and Günnemann, S · 2019
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Fercoq, O., Akian, M., Bouhtou, M., and Gaubert, S · 2013
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Pagerank optimization by edge selection
Csáji, B. C., Jungers, R. M., and Blondel, V. D · 2014
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Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. J., and Fergus, R · 2014
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Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C · 2015
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BIRDNEST: bayesian inference for ratings-fraud detection
Hooi, B., Shah, N., Beutel, A., Günnemann, S., Akoglu, L., Kumar, M., Makhija, D., and Faloutsos, C · 2016
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Robust spectral clustering for noisy data: Modeling sparse corruptions improves latent embeddings
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Protein interface prediction using graph convolutional networks
Fout, A., Byrd, J., Shariat, B., and Ben-Hur, A · 2017
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Chen, J., Wu, Y., Lin, X., and Xuan, Q · 2019
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Graph adversarial training: Dynamically regularizing based on graph structure
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Fast graph representation learning with pytorch geometric
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Hoang, N., Choong, J. J., and Murata, T · 2019
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Virtual adversarial training on graph convolutional networks in node classification
Sun, K., Guo, H., Zhu, Z., and Lin, Z · 2019
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Robust graph neural network against poisoning attacks via transfer learning
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Fdgars: Fraudster detection via graph convolutional networks in online app review system
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Adversarial robustness of similarity-based link prediction
Zhou, K., Michalak, T. P., and Vorobeychik, Y · 2019
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Robust graph convolutional networks against adversarial attacks
Zhu, D., Zhang, Z., Cui, P., and Zhu, W · 2019
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Adversarial attacks on graph neural networks via meta learning
Zügner, D. and Günnemann, S · 2019
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Certifiable robustness and robust training for graph convolutional networks
Zügner, D. and Günnemann, S · 2019
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