ALS (Alternating Least Squares)
GPTKB entity
Statements (27)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:canBe |
sparse data
|
| gptkbp:canBeParallelized |
yes
|
| gptkbp:category |
gptkb:machine_learning
linear algebra numerical optimization |
| gptkbp:convergesTo |
local minimum
|
| gptkbp:firstPublished |
1982
|
| https://www.w3.org/2000/01/rdf-schema#label |
ALS (Alternating Least Squares)
|
| gptkbp:implementedIn |
gptkb:Apache_Spark_MLlib
|
| gptkbp:input |
user-item matrix
|
| gptkbp:optimizedFor |
alternating optimization
|
| gptkbp:output |
latent factors
|
| gptkbp:proposedBy |
C. C. Paige and M. A. Saunders
|
| gptkbp:relatedTo |
gptkb:Singular_Value_Decomposition
gradient descent |
| gptkbp:requires |
regularization
initialization |
| gptkbp:solvedBy |
least squares problem
|
| gptkbp:usedBy |
Netflix Prize competitors
|
| gptkbp:usedFor |
explicit feedback data
implicit feedback data |
| gptkbp:usedIn |
recommender systems
collaborative filtering matrix factorization |
| gptkbp:bfsParent |
gptkb:Apache_Spark_MLlib
|
| gptkbp:bfsLayer |
8
|