Collaborative Metric Learning

Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge Belongie, Deborah Estrin
2017 Proceedings of the 26th International Conference on World Wide Web - WWW '17  
Metric learning algorithms produce distance metrics that capture the important relationships among data. In this work we study the connection between metric learning and collaborative filtering. We propose Collaborative Metric Learning (CML) which learns a joint metric space to encode not only users' preferences but also the user-user and itemitem similarity. The proposed algorithm outperforms stateof-the-art collaborative filtering algorithms on a wide range of recommendation tasks and
more » ... the underlying spectrum of users' fine-grained preferences. CML also achieves significant speedup for Top-K recommendation tasks using off-the-shelf, approximate nearest-neighbor search, with negligible accuracy reduction.
doi:10.1145/3038912.3052639 dblp:conf/www/HsiehYCLBE17 fatcat:xco5r7gptjdq3lqugyzfopzvzm