LiMAML: Personalization of Deep Recommender Models via Meta Learning

Author:

Wang Ruofan1ORCID,Prabhakar Prakruthi1ORCID,Srivastava Gaurav1ORCID,Wang Tianqi1ORCID,Jalali Zeinab S.1ORCID,Bharill Varun1ORCID,Ouyang Yunbo1ORCID,Nigam Aastha1ORCID,Venugopalan Divya1ORCID,Gupta Aman1ORCID,Borisyuk Fedor1ORCID,Keerthi Sathiya1ORCID,Muralidharan Ajith2ORCID

Affiliation:

1. LinkedIn Corporation, Sunnyvale, CA, USA

2. Aliveo AI Corp, Sunnyvale, CA, USA

Publisher

ACM

Reference33 articles.

1. Yi Wang Aden. 2012. KDD Cup 2012 Track 2. https://kaggle.com/competitions/kddcup2012-track2

2. Wide & Deep Learning for Recommender Systems

3. Sequential Scenario-Specific Meta Learner for Online Recommendation

4. Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. In Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 70), Doina Precup and Yee Whye Teh (Eds.). PMLR, 1126--1135. https://proceedings.mlr.press/v70/finn17a.html

5. Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He. 2017. Accurate, large minibatch sgd: Training imagenet in 1 hour. arXiv preprint arXiv:1706.02677 (2017).

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