1. Abernethy, J. D., Bartlett, P. L., Rakhlin, A., & Tewari, A. (2008). Optimal stragies and minimax lower bounds for online convex games. In Proceedings of the 21st annual conference on learning theory (pp. 415–424).
2. Agarwal, A., Hazan, E., Kale, S., & Schapire, R. E. (2006). Algorithms for portfolio management based on the Newton method. In Proceedings of the 23rd international conference on machine learning (pp. 9–16).
3. Agarwal, A., Dekel, O., & Xiao, L. (2010). Optimal algorithms for online convex optimization with multi-point bandit feedback. In Proceedings of the 23rd annual conference on learning theory (pp. 28–40).
4. Blum, A., & Kalai, A. (1999). Universal portfolios with and without transaction costs. Machine Learning, 35(3), 193–205.
5. Cesa-Bianchi, N., & Lugosi, G. (2006). Prediction, learning, and games. Cambridge University Press.