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A5087663077
Research Areas
- Advanced Bandit Algorithms Research
- Human Pose and Action Recognition
- Recommender Systems and Techniques
- Textile materials and evaluations
Sequential models that encode user activity for next action prediction have become a popular design choice building web-scale personalized recommendation systems. Traditional methods of sequential either utilize end-to-end learning on realtime actions, or learn representations separately in an offline batch-generated manner. This paper (1) presents Pinterest's ranking architecture Homefeed, our product and the largest engagement surface; (2) proposes TransAct, model extracts users'...
10.1145/3580305.3599918
article
EN
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
2023-08-04
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