Regression on SONG
0.42Run Time (min)FM-GP
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| FM-GPd=90, n=5133452026.05 | 0.42 | — | — | — | |
| Vard=90, n=5133452026.05 | 1.75 | — | — | — | |
| GPnnd=90, n=5133452026.05 | 2.25 | — | — | — | |
| SGPRn (Samples)=329820, d (Dimensions)=90, GPU Type=Tesla V100-SXM2-32GB, Feature Transformation=ECDF, Precision=Pnew2022.10 | 7.89 | 1.213 | 0.803 | — | |
| BTEn (Samples)=329820, d (Dimensions)=90, GPU Type=Tesla V100-SXM2-16GB, Feature Transformation=ECDF, Precision=Pnew2022.10 | 11.5 | 1.306 | 0.894 | — | |
| BTn (Samples)=329820, d (Dimensions)=90, GPU Type=Tesla V100-SXM2-16GB, Feature Transformation=ECDF, Precision=Pnew2022.10 | 11.6 | 1.331 | 0.904 | — | |
| SVGPNoise Level=Standard2023.06 | 24.7 | 1.22 | 0.81 | — | |
| MATÉRN (BBMM)n (Samples)=329820, d (Dimensions)=90, GPU Type=Tesla V100-SXM2-32GB, Feature Transformation=ECDF, Precision=Pnew2022.10 | 33.79 | 1.206 | 0.807 | — | |
| SVGPn (Samples)=329820, d (Dimensions)=90, GPU Type=Tesla V100-SXM2-32GB, Feature Transformation=ECDF, Precision=Pnew2022.10 | 39.55 | 1.417 | 0.998 | — | |
| CGNoise Level=Standard2023.06 | 195 | 1.36 | 0.85 | — | |
| SGD-GPNoise Level=Standard2023.06 | 220 | 1.21 | 0.8 | — | |
| CGNoise Level=Low2023.06 | — | — | — | 0.83 | |
| SGD-GPNoise Level=Low2023.06 | — | — | — | 0.8 |