acmtf_gradient: Calculate gradient of ACMTF model.

In CMTFtoolbox: Create (Advanced) Coupled Matrix and Tensor Factorization Models

Calculate gradient of ACMTF model.

Description

Calculate gradient of ACMTF model.

Usage

acmtf_gradient(
  x,
  Z,
  alpha = 1,
  beta = rep(0.001, length(Z$object)),
  epsilon = 1e-08
)

Arguments

x	Vectorized parameters of the CMTF model.
Z	Z object as generated by setupCMTFdata().
alpha	Alpha value of the loss function as specified by Acar et al., 2014
beta	Beta value of the loss function as specified by Acar et al., 2014
epsilon	Epsilon value of the loss function as specified by Acar et al., 2014

Value

Vectorized gradient of the ACMTF model.

Examples

A = array(rnorm(108*2), c(108, 2))
B = array(rnorm(100*2), c(100, 2))
C = array(rnorm(10*2), c(10, 2))
D = array(rnorm(100*2), c(100,2))
E = array(rnorm(10*2), c(10,2))

df1 = reinflateTensor(A, B, C)
df2 = reinflateTensor(A, D, E)
datasets = list(df1, df2)
modes = list(c(1,2,3), c(1,4,5))
Z = setupCMTFdata(datasets, modes, normalize=FALSE)

init = initializeACMTF(Z, 2, output="vect")
g = acmtf_gradient(init, Z)

CMTFtoolbox documentation built on Aug. 23, 2025, 1:11 a.m.