Counterfactual Learning and Evaluation for Recommender Systems:
RecSys 2021 Counterfactual Learning and Evaluation for Recommender Systems: Foundations, Implementations, and Recent Advances by Yuta Saito (Cornell University, USA) and Thorsten Joachims (Cornell University, USA) https://recsys.acm.org/recsys21/tutor...
▶︎
Multi-Modal Recommender Systems: Hands-On Exploration
▶︎
Keynote Xavier Amatriain
▶︎
RecSys 2020 Tutorial: Introduction to Bandits in Recommender Systems
▶︎
Susan Athey: Machine Learning and Causal Inference for Personalization
▶︎
Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026
▶︎
Counterfactual Evaluation and Learning from Logged User Feedback
▶︎
The Power of a Single Neuron and a Path to Simulating the Brain | Dr. Konrad Kording
▶︎
Spotify ML Question - Design a Recommendation System (Full mock interview)
▶︎
Stanford CS224W: Machine Learning w/ Graphs I 2023 I GNNs for Recommender Systems
▶︎
Don't learn AI Agents without Learning these Fundamentals
▶︎
RecSys 2020 Tutorial: Feature Engineering for Recommender Systems
▶︎
Training Sand to Think: Artificial General Intelligence & Future of Physics
▶︎
Richard Sutton - The future of AI - IPAM at UCLA
▶︎
Tutorial 2B Hands On Reinforcement Learning for recommender systems
▶︎
Visualizing transformers and attention | Talk for TNG Big Tech Day '24
▶︎
How GPT, Claude, and Gemini are actually trained and served – Reiner Pope
▶︎
Unlocking Graph Neural Networks: A Hands-On Journey From Basics To Breakthroughs
▶︎
Recent Advances in Generative Conversational Recommender Systems
▶︎
RecSys 2016: Tutorial on Lessons Learned from Building Real-life Recommender Systems
▶︎