probabilistic matrix factorization (extensions of models)
TRANSCRIPT
Part 1: Models and Representations
Session 1:- Probabilistic Matrix Factorization- Poisson Models (CF and Content-based)
Session 2:- Adding trust/side information- Bayesian extensions- Poisson Models (trust/social)- LGM (intro)
Session 3:- State-space models- Tensor-Factorization- Time-dependent
Approximate and Scalable Inference for Complex Probabilistic Models in Recommender Systems