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Recommender Systems Courses

Fair Recommendations with Limited Sensitive Attributes - A Distributionally Robust Optimization Approach
Association for Computing Machinery (ACM) via YouTube
Going Beyond Popularity and Positivity Bias: Correcting Multifactorial Bias in Recommender Systems - M1.7
Association for Computing Machinery (ACM) via YouTube
CaDRec: Contextualized and Debiased Recommender Model - Fairness in RecSys
Association for Computing Machinery (ACM) via YouTube
Reinforcement Learning-based Recommender Systems with Large Language Models - SIGIR 2024
Association for Computing Machinery (ACM) via YouTube
Fair Sequential Recommendation without User Demographics - SIGIR 2024
Association for Computing Machinery (ACM) via YouTube
Data-efficient Fine-tuning for LLM-based Recommendation - SIGIR 2024 M1.6
Association for Computing Machinery (ACM) via YouTube
IDGenRec: LLM-RecSys Alignment with Textual ID Learning - Lecture 1
Association for Computing Machinery (ACM) via YouTube
Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance - Evaluation M1.5
Association for Computing Machinery (ACM) via YouTube
Enhancing Sequential Recommenders with Augmented Knowledge from Aligned LLMs - SIGIR 2024
Association for Computing Machinery (ACM) via YouTube
Supercharging Recommender Systems - Unleashing the Power of Distributed Model Training
MLOps World: Machine Learning in Production via YouTube
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