1. Rogers, A., Hosur Ananthakrishna, S., Rumshisky, A.: What’s in your embedding, and how it predicts task performance. In: Proceedings of the 27th International Conference on Computational Linguistics, Santa Fe, New Mexico, USA, Association for Computational Linguistics, pp. 2690–2703, August 2018
2. Senel, L.K., Utlu, I., Yucesoy, V., Koc, A., Cukur, T.: Semantic structure and interpretability of word embeddings. arXiv preprint arXiv:1711.00331 (2017)
3. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, New York (2006)
4. Torralba, A., Efros, A.A.: Unbiased look at dataset bias. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1521–1528. IEEE (2011)
5. Hardt, M., Price, E., Srebro, N., et al.: Equality of opportunity in supervised learning. In: Advances in Neural Information Processing Systems, pp. 3315–3323 (2016)