1. Abdulrahman, S.M., Brazdil, P.: Measures for combining accuracy and time for meta-learning. In: Meta-Learning and Algorithm Selection Workshop at ECAI 2014, pp. 49–50 (2014)
2. Abdulrahman, S.M., Brazdil, P., van Rijn, J.N., Vanschoren, J.: Speeding up algorithm selection using average ranking and active testing by introducing runtime. Mach. Learn. 1, 37–66 (2017). Special Issue on Metalearning and Algorithm Selection
3. Bergstra, J.S., Bardenet, R., Bengio, Y., Kégl, B.: Algorithms for hyper-parameter optimization. In: Advances in Neural Information Processing Systems, pp. 2546–2554 (2011)
4. Brazdil, P., Giraud-Carrier, C., Soares, C., Vilalta, R.: Metalearning: Applications to Data Mining. Springer Science & Business Media (2008)
5. Brazdil, P., Soares, C., da Costa, J.P.: Ranking learning algorithms: using IBL and meta-learning on accuracy and time results. Mach. Learn. 50(3), 251–277 (2003)