Complete result settings for NLTCS dataset (table columns are sortable)
The experiments are described in Rooshenas and Lowd, Discriminative Structure Learning of Arithmetic Circuits, AIStats 16
| Tree# | C | Max. EM Iteration | Train CLL | Validation CLL | Test CLL | Learning Time |
| 1 | 1.000000 | -1.285655 | -1.285503 | -1.275081 | 10.946102 |
| 1 | 2.000000 | -1.285410 | -1.285786 | -1.275118 | 11.039907 |
| 1 | 0.100000 | -1.291267 | -1.286405 | -1.281418 | 10.571557 |
| 1 | 0.500000 | -1.286450 | -1.281564 | -1.277138 | 10.683495 |
| 1 | 2.000000 | -1.285410 | -1.285786 | -1.275118 | 10.458197 |
| 1 | 0.500000 | -1.286450 | -1.281564 | -1.277138 | 10.679387 |
| 1 | 2.000000 | -1.285410 | -1.285786 | -1.275118 | 10.810316 |
| 1 | 1.000000 | -1.285655 | -1.285503 | -1.275081 | 10.540251 |
| 1 | 1.000000 | -1.285655 | -1.285503 | -1.275081 | 10.869640 |
| 1 | 0.500000 | -1.286450 | -1.281564 | -1.277138 | 10.397479 |
| 1 | 0.100000 | -1.291267 | -1.286405 | -1.281418 | 10.104987 |
| 1 | 0.100000 | -1.291267 | -1.286405 | -1.281418 | 10.967054 |
| 1 | 2.000000 | 10 | -1.285410 | -1.285786 | -1.275118 | 11.045547 |
| 1 | 0.500000 | 10 | -1.286450 | -1.281564 | -1.277138 | 10.870104 |
| 1 | 0.100000 | 10 | -1.291267 | -1.286405 | -1.281418 | 10.693736 |
| 1 | 1.000000 | 10 | -1.285655 | -1.285503 | -1.275081 | 11.025895 |
| 1 | 0.500000 | 20 | -1.286450 | -1.281564 | -1.277138 | 10.819450 |
| 1 | 2.000000 | 20 | -1.285410 | -1.285786 | -1.275118 | 11.136755 |
| 1 | 1.000000 | 20 | -1.285655 | -1.285503 | -1.275081 | 11.233824 |
| 1 | 2.000000 | 50 | -1.285410 | -1.285786 | -1.275118 | 10.392185 |
| 1 | 0.100000 | 20 | -1.291267 | -1.286405 | -1.281418 | 10.529632 |
| 1 | 1.000000 | 50 | -1.285655 | -1.285503 | -1.275081 | 10.687512 |
| 1 | 0.500000 | 50 | -1.286450 | -1.281564 | -1.277138 | 10.880909 |
| 1 | 0.100000 | 50 | -1.291267 | -1.286405 | -1.281418 | 10.737304 |
| 2 | 0.100000 | 10 | -1.279661 | -1.279925 | -1.270488 | 2081.033569 |
| 2 | 0.500000 | 10 | -1.269106 | -1.276372 | -1.265041 | 2219.487689 |
| 2 | 2.000000 | 10 | -1.267013 | -1.277507 | -1.262191 | 2249.309195 |
| 2 | 1.000000 | 10 | -1.268003 | -1.276948 | -1.262972 | 2263.292888 |
| 3 | 0.100000 | 10 | -1.275340 | -1.278306 | -1.269796 | 3947.548296 |
| 3 | 0.500000 | 10 | -1.263901 | -1.278053 | -1.261744 | 4034.774026 |
| 3 | 2.000000 | 10 | -1.259926 | -1.277792 | -1.264573 | 4060.330826 |
| 2 | 0.100000 | 20 | -1.277941 | -1.278558 | -1.268562 | 4076.934156 |
| 3 | 1.000000 | 10 | -1.261153 | -1.277877 | -1.264962 | 4088.142517 |
| 2 | 0.500000 | 20 | -1.268319 | -1.275138 | -1.263650 | 4388.382625 |
| 2 | 1.000000 | 20 | -1.267079 | -1.276543 | -1.263014 | 4444.075292 |
| 2 | 2.000000 | 20 | -1.265916 | -1.276766 | -1.261550 | 5765.835526 |
| 4 | 2.000000 | 10 | -1.256121 | -1.275034 | -1.263446 | 6176.447686 |
| 4 | 0.500000 | 10 | -1.259139 | -1.274823 | -1.262563 | 6240.044862 |
| 4 | 1.000000 | 10 | -1.257454 | -1.274795 | -1.262563 | 6249.084570 |
| 4 | 0.100000 | 10 | -1.273402 | -1.278938 | -1.267716 | 7054.874063 |
| 3 | 0.100000 | 20 | -1.273475 | -1.276569 | -1.267317 | 7751.635027 |
| 3 | 1.000000 | 20 | -1.258252 | -1.277522 | -1.265833 | 7942.646876 |
| 3 | 0.500000 | 20 | -1.260476 | -1.279676 | -1.260493 | 8043.516538 |
| 3 | 2.000000 | 20 | -1.257278 | -1.276844 | -1.265534 | 8161.742861 |
| 2 | 0.100000 | 50 | -1.277291 | -1.278940 | -1.267385 | 10050.667080 |
| 2 | 2.000000 | 50 | -1.265320 | -1.277453 | -1.260966 | 10694.678269 |
| 2 | 0.500000 | 50 | -1.265098 | -1.273092 | -1.258782 | 10714.440106 |
| 2 | 1.000000 | 50 | -1.265885 | -1.277306 | -1.263582 | 10859.281359 |
| 4 | 1.000000 | 20 | -1.254513 | -1.272162 | -1.263406 | 12134.090945 |
| 4 | 0.500000 | 20 | -1.255938 | -1.276946 | -1.260270 | 12180.724574 |
| 4 | 0.100000 | 20 | -1.270420 | -1.276955 | -1.264466 | 12180.042475 |
| 4 | 2.000000 | 20 | -1.252755 | -1.272537 | -1.264625 | 12402.701262 |
| 3 | 0.100000 | 50 | -1.272959 | -1.276140 | -1.265257 | 19001.840405 |
| 3 | 1.000000 | 50 | -1.257517 | -1.276825 | -1.264174 | 19629.862409 |
| 3 | 0.500000 | 50 | -1.259167 | -1.278734 | -1.259780 | 19879.782748 |
| 3 | 2.000000 | 50 | -1.256155 | -1.278237 | -1.264266 | 20047.355254 |
| 4 | 0.100000 | 50 | -1.269390 | -1.275715 | -1.263097 | 29521.869843 |
| 4 | 1.000000 | 50 | -1.251682 | -1.275266 | -1.260659 | 29937.420524 |
| 4 | 0.500000 | 50 | -1.253026 | -1.277781 | -1.258180 | 30006.368577 |
| 4 | 2.000000 | 50 | -1.250020 | -1.277667 | -1.261639 | 30271.829989 |