Hyperparameters for EASER
We tested the following hyperparameter space:
Parameter |
Ranges |
l2_norm |
[loguniform, 2.72, 16] |
Dataset |
l2_norm |
MovieLens 1M |
696.785 |
Amazon Digital Music |
15.930 |
Epinions |
174.179 |
Hyperparameters for MultiDAE
We tested the following hyperparameter space:
Parameter |
Ranges |
Epoch |
[20, 30, 40] |
Learning Rate |
[0.0001, 0.0005,0.003, 0.001] |
Batch Size |
[32, 64, 128, 256, 512] |
intermediate_dim |
600 |
Latent_dim |
[100, 200, 300] |
Reg_lambda |
0.01 |
Dropout_pkeep |
1 |
Dataset |
Epoch |
Learning Rate |
Batch Size |
Intermediate_dim |
Latent_dim |
Reg_lambda |
Dropout_pkeep |
MovieLens 1M |
20 |
0.0005 |
128 |
600 |
100 |
0.01 |
1 |
Amazon Digital Music |
40 |
0.0005 |
512 |
600 |
300 |
0.01 |
1 |
Epinions |
40 |
0.0005 |
512 |
600 |
300 |
0.01 |
1 |
Hyperparameters for MultiVAE
Dataset |
Epoch |
Learning Rate |
Batch Size |
Intermediate_dim |
Latent_dim |
Reg_lambda |
Dropout_pkeep |
MovieLens 1M |
- |
- |
- |
- |
- |
- |
- |
Amazon Digital Music |
- |
- |
- |
- |
- |
- |
- |
Epinions |
- |
- |
- |
- |
- |
- |
- |
Hyperparameters for GMF
We tested the following hyperparameter space:
Parameter |
Ranges |
Epochs |
[30, 40, 50] |
Learning Rate |
[0.0001, 0.0005, 0.001] |
Batch Size |
[128, 256, 512] |
Mf_factors |
[8, 16, 32, 64, 128, 256] |
Is_edge_weight_train |
True |
Dataset |
Epochs |
Learning Rate |
Batch Size |
Mf_factors |
Is_edge_weight_train |
MovieLens 1M |
40 |
512 |
128 |
0.00014 |
true |
Amazon Digital Music |
50 |
256 |
256 |
0.00054 |
true |
Epinions |
40 |
512 |
256 |
0.00035 |
True |
Hyperparameters for NeuMF
We tested the following hyperparameter space:
Parameter |
Ranges |
Epoch |
[quniform, 30, 100, 1] |
Learning rate |
[loguniform, -11.512925464970229, 0] |
Mf_factors |
[64, 128, 256] |
Batch Size |
[64, 128, 256] |
Dropout |
0 |
Is_mf_train |
True |
Is_mlp_train |
True |
m |
[4,6,8] |
Dataset |
Epoch |
Learning rate |
Mf_factors |
Batch Size |
Dropout |
Is_mf_train |
Is_mlp_train |
m |
MovieLens 1M |
- |
- |
- |
- |
- |
- |
- |
- |
Amazon Digital Music |
- |
- |
- |
- |
- |
- |
- |
- |
Epinions |
- |
- |
- |
- |
- |
- |
- |
- |
Hyperparameters for ConvNeuMF
We tested the following hyperparameter space:
Parameter |
Ranges |
Epoch |
[20, 30] |
Learning Rate |
[0.0001, 0.0005, 0.001] |
Batch Size |
[16, 32] |
Embedding Size |
[16, 32] |
l_w |
[0.0001, 0.001, 0.0005] |
l_b |
[0.01, 0.001,0.0001, 0.00001] |
Dropout |
[0.1,0.2,0.3, 0.4, 0.5] |
Dataset |
Epoch |
Learning Rate |
Batch Size |
Embedding Size |
l_w |
l_b |
Dropout |
MovieLens 1M |
30 |
0.0005 |
16 |
32 |
0.0001 |
0.01 |
0.7 |
Amazon Digital Music |
30 |
0.0005 |
16 |
32- |
0.0005 |
0.001 |
0.5 |
Epinions |
25 |
0.0001 |
16 |
100 |
0.1 |
0.001 |
0.45 |
Hyperparameters for ConvMF
Parameter |
Ranges |
Epoch |
[20, 30] |
Learning Rate |
[0.0001, 0.0005, 0.001, 0.003] |
Batch Size |
[50, 64, 100] |
Embedding Size |
[64, 128, 256] |
l_w |
[0.0001, 0.001, 0.0005] |
l_b |
[0.01, 0.001,0.0001, 0.00001] |
Dropout |
[0.1,0.2,0.3, 0.4, 0.5] |
Dataset |
Epoch |
Learning Rate |
Batch Size |
Embedding Size |
l_w |
l_b |
Dropout |
MovieLens 1M |
25 |
0.0001 |
32 |
100 |
0.001 |
0.00001 |
0.2 |
Amazon Digital Music |
25 |
0.0001 |
16 |
64 |
0.001 |
0.00001 |
0.2 |
Epinions |
25 |
0.0001 |
16 |
100 |
0.1 |
0.001 |
0.45 |
Hyperparameters for NGCF
We tested the following hyperparameter space:
Parameter |
Options |
Learning rate |
[0.0001, 0.0005, 0.001, 0.003] |
Epoch |
[30, 40, 50] |
Batch Size |
[64, 128, 256, 512] |
Factors |
[8, 16, 32, 64, 128, 256] |
Node_dropout |
[0.1,0.2, 0.3, 0.45, 0.5] |
Message_dropout |
[0.1,0.2, 0.3, 0.45, 0.5] |
Dataset |
Epoch |
Learning Rate |
Batch Size |
Factors |
MovieLens 1M |
30 |
0.0002 |
512 |
64 |
Amazon Digital Music |
40 |
0.00005 |
256 |
32 |
Epinions |
50 |
0.0002 |
512 |
8 |