1. Babbar, R., Schölkopf, B. (2017). Dismec: Distributed sparse machines for extreme multi-label classification. In Proceedings of the tenth ACM international conference on web search and data mining (pp. 721–729). ACM.
2. Balntas, V., Riba, E., Ponsa, D., & Mikolajczyk, K. (2016). Learning local feature descriptors with triplets and shallow convolutional neural networks. In British machine vision conference (pp. 119.1–119.11).
3. Bengio, Y., Ducharme, R., Vincent, P., & Jauvin, C. (2003). A neural probabilistic language model. Journal of Machine Learning Research, 3, 1137–1155.
4. Bertinetto, L., Henriques, J. F., Valmadre, J., Torr, P. H. S., & Vedaldi, A. (2016). Learning feed-forward one-shot learners. In Neural information processing systems (pp. 523–531).
5. Bhatia, K., Jain, H., Kar, P., Varma, M., & Jain, P. (2015). Sparse local embeddings for extreme multi-label classification. In Advances in neural information processing systems (pp. 730–738).