RecSys ML
Sharing knowledge of the industrial state of the art in #recommendersystems and applied #machinelearning
Please find detailed content in https://recsysml.substack.com/
Recsys Retrieval ~ LLM Pretraining / SFT
Understanding the Ranking Model in a Recommender System
Generative people recommendations based on OneRec
Reinforcement Learning to maximize online ad revenue without retention tradeoffs
Generative retrieval GenAI meets recommender systems
Friend Recommendations Retrieval From Graph Search to Embedding based
Declarative Value Model Tuning
Ranking model calibration in recommender systems
Entrypoint retention modeling in recommender systems
Optimizing Session Value in Recommender Systems Feed construction 3/3
Optimizing Session Value in Recommender Systems Inspiration from finance 2/3
Optimizing Session Value in Recommender Systems Overview 1/3
User Embeddings in Recommender Systems 3/6
User Embeddings in Recommender Systems 1/6
User Embeddings in Recommender Systems 5/6
User Embeddings in Recommender Systems 4/6
User Embeddings in Recommender Systems 6/6
User Embeddings in Recommender Systems 2/6
Causal Debiasing in Recommender Systems to reduce popularity bias 2/2
Causal Debiasing in Recommender Systems to reduce popularity bias 1/2
Code: Knowledge Distillation to train Early Ranker from Final Ranker 2/2
Code: Knowledge Distillation to train Early Ranker from Final Ranker 1/2
Using Machine Learning to Build a Delightful Notification Experience