Graph active learning for GCN-based zero-shot classification

R. Abel, Y. Louzoun, Regional based query in graph active learning, 2019, arXiv preprint arXiv:1906.08541. M. Bilgic, L. Mihalkova, L. Getoor, Active learning for networked data, in: Proceedings of the 27th international conference on machine learning (ICML-10), 2010, pp. 79–86. H. Cai, V.W. Zheng, K.C.C. Chang, Active learning for graph embedding, 2017, arXiv preprint arXiv:1705.05085. Deng, 2014, Large-scale object classification using label relation graphs, 48 Frome, 2013, Devise: A deep visual-semantic embedding model, 2121 Gavves, 2015, Active transfer learning with zero-shot priors: reusing past datasets for future tasks, 2731 Gutman, 2006, Laplacian energy of a graph, Linear Algebra and its Applications, 414, 29, 10.1016/j.laa.2005.09.008 Hanneke, 2014, Theory of active learning, Foundations and Trends in Machine Learning, 7, 10.1561/2200000037 He, 2016, Deep residual learning for image recognition, 770 N. Houlsby, F. Huszár, Z. Ghahramani, M. Lengyel, Bayesian active learning for classification and preference learning, 2011, arXiv preprint arXiv:1112.5745. P. Hu, Z.C. Lipton, A. Anandkumar, D. Ramanan, Active learning with partial feedback, 2018, arXiv preprint arXiv:1802.07427. Ji, 2012, A variance minimization criterion to active learning on graphs, Artificial Intelligence and Statistics, 556 Ji, 2019, Class-specific synthesized dictionary model for zero-shot learning, Neurocomputing, 329, 339, 10.1016/j.neucom.2018.10.069 T.N. Kipf, M. Welling, Semi-supervised classification with graph convolutional networks, 2016, arXiv preprint arXiv:1609.02907. Lampert, 2013, Attribute-based classification for zero-shot visual object categorization, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 453, 10.1109/TPAMI.2013.140 H. Larochelle, D. Erhan, Y. Bengio, Zero-data learning of new tasks., in: AAAI, 2008, p. 3. Lee, 2018, Multi-label zero-shot learning with structured knowledge graphs, 1576 Lei Ba, 2015, Predicting deep zero-shot convolutional neural networks using textual descriptions, 4247 Li, 2014, Attributes make sense on segmented objects, 350 Long, 2017, From zero-shot learning to conventional supervised classification: unseen visual data synthesis, 1627 X. Lu, W. Wang, M. Danelljan, T. Zhou, J. Shen, L. Van Gool, Video object segmentation with episodic graph memory networks, 2020, arXiv preprint arXiv:2007.07020. Mensink, 2014, Costa: Co-occurrence statistics for zero-shot classification, 2441 Miller, 1995, Wordnet: a lexical database for english, Communications of the ACM, 38, 39, 10.1145/219717.219748 M. Norouzi, T. Mikolov, S. Bengio, Y. Singer, J. Shlens, A. Frome, G.S. Corrado, J. Dean, Zero-shot learning by convex combination of semantic embeddings, 2013, arXiv preprint arXiv:1312.5650. Pachori, 2018, Hashing in the zero shot framework with domain adaptation, Neurocomputing, 275, 2137, 10.1016/j.neucom.2017.10.061 Palatucci, 2009, Zero-shot learning with semantic output codes, 1410 Pennington, 2014, Glove: Global vectors for word representation, 1532 Qi, 2018, Learning human-object interactions by graph parsing neural networks, 401 Qi, 2013, Terrorist networks, network energy and node removal: a new measure of centrality based on laplacian energy, Social Networking, 2, 19, 10.4236/sn.2013.21003 Radovanović, 2010, Hubs in space: popular nearest neighbors in high-dimensional data, Journal of Machine Learning Research, 11, 2487 Russakovsky, 2015, Imagenet large scale visual recognition challenge, International Journal of Computer Vision, 115, 211, 10.1007/s11263-015-0816-y O. Sener, S. Savarese, Active learning for convolutional neural networks: A core-set approach, 2017, arXiv preprint arXiv:1708.00489. B. Settles, Active learning literature survey, Technical Report, University of Wisconsin-Madison Department of Computer Sciences, 2009. Settles, 2012, Active learning, Synthesis Lectures on Artificial Intelligence and Machine Learning, 6, 1, 10.1007/978-3-031-01560-1 Wang, 2019, Zero-shot video object segmentation via attentive graph neural networks, 9236 Wang, 2019, A survey of zero-shot learning: settings, methods, and applications, ACM Transactions on Intelligent Systems and Technology (TIST), 10, 13 Wang, 2020, Hierarchical human parsing with typed part-relation reasoning, 8929 Wang, 2018, Zero-shot recognition via semantic embeddings and knowledge graphs, 6857 Y. Wu, Y. Xu, A. Singh, Y. Yang, A. Dubrawski, Active learning for graph neural networks via node feature propagation, 2019, arXiv preprint arXiv:1910.07567. Wu, 2019 Xie, 2019, Attentive region embedding network for zero-shot learning Xie, 2020, Region graph embedding network for zero-shot learning Xie, 2017, Active zero-shot learning: a novel approach to extreme multi-labeled classification, International Journal of Data Science and Analytics, 3, 151, 10.1007/s41060-017-0042-5 Zheng, 2009, Cross-domain activity recognition, 61