AI engineering glossary · Time series recsys
What is ALS (alternating least squares)?
Alternating least squares (also called ALS): A method for matrix factorisation that alternates between fixing item vectors and solving for user vectors in closed form, then the reverse. Each step is a set of independent least-squares problems, so it parallelises well and suits implicit feedback data.
Alternating least squares: an example
Fix the item factors, solve each user's vector; fix the user factors, solve each item's; repeat about 10 to 15 times.
Related terms
More Time series recsys terms
- Anomaly detection (time series)
- ARCH model
- ARIMA
- ARIMAX
- ARMA
- Augmented Dickey-Fuller test
- Autocorrelation
- Autocorrelation function
Where you learn it
Alternating least squares is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.