Improving Training Stability for Multitask Ranking Models in Recommender Systems

Author:

Tang Jiaxi1ORCID,Drori Yoel2ORCID,Chang Daryl3ORCID,Sathiamoorthy Maheswaran1ORCID,Gilmer Justin1ORCID,Wei Li3ORCID,Yi Xinyang1ORCID,Hong Lichan1ORCID,Chi Ed H.1ORCID

Affiliation:

1. Google Deepmind, Mountain View, CA, USA

2. Google Research, Tel Aviv, Israel

3. Google Inc, Mountain View, CA, USA

Publisher

ACM

Reference36 articles.

1. Martin Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard et al. 2016. Tensorflow: a system for large-scale machine learning.. In OSDI. Savannah GA USA.

2. Rohan Anil, Sandra Gadanho, Da Huang, Nijith Jacob, Zhuoshu Li, Dong Lin, Todd Phillips, Cristina Pop, Kevin Regan, Gil I Shamir, et al. 2022. On the Factory Floor: ML Engineering for Industrial-Scale Ads Recommendation Models. arXiv preprint arXiv:2209.05310 (2022).

3. Newsha Ardalani, Carole-Jean Wu, Zeliang Chen, Bhargav Bhushanam, and Adnan Aziz. 2022. Understanding Scaling Laws for Recommendation Models. arXiv preprint arXiv:2208.08489 (2022).

4. Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016. Layer normalization. arXiv preprint arXiv:1607.06450 (2016).

5. Latent Cross

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