Funder
Natural Sciences and Engineering Research Council of Canada
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Reference84 articles.
1. Agarwal, A., Negahban, S., & Wainwright, M. J. (2012). Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions. The Annals of Statistics, 40(2), 1171–1197.
2. Ando, R. K., & Zhang, T. (2005). A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6(61), 1817–1853.
3. Argyriou, A., Evgeniou, T., & Pontil, M. (2006). Multi-task feature learning. In: Proceedings of the 19th international conference on neural information processing systems. MIT Press, Cambridge, MA, USA, NIPS’06, pp. 41–48.
4. Bach, F. R. (2008). Consistency of the group lasso and multiple kernel learning. Journal of Machine Learning Research, 9(40), 1179–1225.
5. Bai, H., Zhong, Y., Gao, X., et al. (2020). Multivariate mixed response model with pairwise composite-likelihood method. Stats, 3(3), 203–220.
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