GitHub

References

[1]
S. Mandlı́k, M. Racinsky, V. Lisý and T. Pevný. JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data. J. Mach. Learn. Res. 23, 298:1–298:5 (2022).
[2]
T. Pevný and P. Somol. Discriminative models for multi-instance problems with tree-structure. CoRR abs/1703.02868 (2017), arXiv:1703.02868.
[3]
T. Pevný and P. Somol. Using Neural Network Formalism to Solve Multiple-Instance Problems. In: Advances in Neural Networks - ISNN 2017 - 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21-26, 2017, Proceedings, Part I, Vol. 10261 of Lecture Notes in Computer Science, edited by F. Cong, A. Leung and Q. Wei (Springer, 2017); pp. 135–142.
[4]
Š. Mandlík and T. Pevný. Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks. Master's thesis, Czech Technical University (2020), https://dspace.cvut.cz/handle/10467/87851?locale-attribute=en.
[5]
T. G. Dietterich, R. H. Lathrop and T. Lozano-Pérez. Solving the Multiple Instance Problem with Axis-Parallel Rectangles. Artif. Intell. 89, 31–71 (1997).
[6]
[7]
R. A. Fisher. The use of multiple measurements in taxonomic problems. Annals of eugenics 7, 179–188 (1936).
[8]
O. Z. Kraus, L. J. Ba and B. J. Frey. Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning. CoRR abs/1511.05286 (2015), arXiv:1511.05286.
[9]
Gülçehre, K. Cho, R. Pascanu and Y. Bengio. Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks. In: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I, Vol. 8724 of Lecture Notes in Computer Science, edited by T. Calders, F. Esposito, E. Hüllermeier and R. Meo (Springer, 2014); pp. 530–546.
[10]