Cold-start Active Learning with Robust Ordinal Matrix Factorization

By Neil Houlsby, José Miguel Hernández-Lobato, Zoubin Ghahramani. 2014

85 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Adam Trischler
2. Alessandro Sordoni
3. Philip Bachman
4. Jianfeng Gao
5. Yoshua Bengio
6. Zhe Gan
7. Mohit Bansal
8. Kyunghyun Cho

Citations in the corpus

• Learning Algorithms for Active Learning (2017, methodology): “Pro-posals for learning an adaptive selection strategy have been made in the form of Bayesian methods that learn the parameters of a user model (Houlsby et al., 2014; Harpale & Yang, 2008), and in the form of decision-trees learned from existing ratings (Sun et al., 2013b).”