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

Split Penalty Standard Deviation L1 Penalty Initial Evidence Train CLL Validation CLL Test CLL Node# Edge# Feature# Learning Time
5 0.5 2 8 -2.779265 -2.696851 -2.776125 1117 2449 280 17.307368
5 0.5 1 8 -2.777351 -2.697695 -2.776709 1045 2079 280 17.288371
5 0.5 0.1 8 -2.778111 -2.699864 -2.776752 1133 2448 284 18.012261
5 0.5 0.5 8 -2.775661 -2.698945 -2.772773 1012 1966 290 19.266070
5 0.5 0.5 1 -2.779974 -2.706102 -2.782605 1777 3467 368 38.869090
5 0.5 2 1 -2.779705 -2.705553 -2.785201 1560 2901 360 41.128747
2 0.5 2 8 -2.765300 -2.694336 -2.774333 1661 3367 426 43.286419
5 0.5 1 1 -2.778135 -2.706818 -2.779583 1748 3341 368 41.577678
5 0.5 0.1 1 -2.776737 -2.705491 -2.781037 1718 3276 374 42.122595
2 0.5 0.1 8 -2.761456 -2.694787 -2.771247 2090 4822 462 50.024395
2 0.5 0.5 8 -2.762236 -2.696362 -2.771006 2058 4720 442 51.458176
2 0.5 1 8 -2.765199 -2.698666 -2.771860 2072 4763 440 59.167005
2 0.5 2 1 -2.768015 -2.699154 -2.777804 2974 5938 538 95.945413
2 0.5 0.5 1 -2.765368 -2.699645 -2.772477 3415 6699 636 133.810656
2 0.5 0.1 1 -2.762591 -2.696486 -2.780496 3427 6664 670 138.368964
2 0.5 1 1 -2.765684 -2.705360 -2.780862 3281 6346 696 150.818071
5 0.1 1 8 -2.778095 -2.700416 -2.774902 994 1941 278 14.256832
5 0.1 2 8 -2.779726 -2.698846 -2.779445 1069 2153 276 15.003718
5 0.1 0.5 8 -2.776535 -2.697358 -2.773806 1039 2072 284 14.532789
5 0.1 2 5 -2.781359 -2.698326 -2.778967 1125 2315 260 14.674768
5 0.1 0.5 5 -2.779010 -2.700973 -2.776777 1303 2930 270 15.223685
5 0.1 1 5 -2.779588 -2.701384 -2.775938 1371 3243 270 17.210383
5 0.5 2 8 -2.779265 -2.696851 -2.776125 1117 2449 280 14.579782
5 0.5 1 8 -2.777351 -2.697695 -2.776709 1045 2079 280 14.527790
5 0.5 0.1 8 -2.778111 -2.699864 -2.776752 1133 2448 284 14.631774
5 0.5 0.5 8 -2.775661 -2.698945 -2.772773 1012 1966 290 15.528638
5 0.1 0.1 8 -2.776230 -2.697636 -2.774045 1105 2345 286 16.272525
5 0.5 1 5 -2.776919 -2.693908 -2.771160 1351 3024 284 16.213534
5 0.1 0.1 5 -2.778641 -2.700760 -2.776300 1489 3518 272 16.639469
5 0.5 2 5 -2.778853 -2.694475 -2.774896 1512 3621 278 17.702308
5 0.5 0.1 5 -2.777999 -2.701282 -2.776407 1483 3535 272 17.546331
5 0.5 0.5 5 -2.776032 -2.697529 -2.774107 1475 3349 286 17.955269
5 0.1 1 1 -2.779111 -2.707469 -2.782788 1669 3208 348 30.081426
2 0.1 2 5 -2.769528 -2.688538 -2.772773 1447 2735 394 31.751173
5 0.1 0.1 1 -2.781956 -2.716061 -2.785997 1668 3191 360 30.460368
5 0.1 0.5 1 -2.780033 -2.710969 -2.782518 1647 3127 368 32.607042
5 0.1 2 1 -2.779285 -2.701305 -2.780647 1646 3158 336 33.112965
2 0.1 1 8 -2.766813 -2.693218 -2.774162 1687 3587 394 34.720721
2 0.5 2 5 -2.767308 -2.696493 -2.776498 1879 4355 396 34.019827
2 0.1 1 5 -2.765459 -2.691766 -2.769036 1910 4082 422 35.030674
2 0.5 2 8 -2.765300 -2.694336 -2.774333 1661 3367 426 38.163197
2 0.1 0.1 8 -2.766806 -2.691786 -2.770552 1617 3254 424 38.542140
2 0.1 0.5 5 -2.765822 -2.690357 -2.772309 2183 4670 430 38.262182
2 0.5 1 5 -2.765495 -2.694644 -2.773108 2023 4644 418 38.561137
2 0.5 0.1 5 -2.764457 -2.695109 -2.775536 1704 3514 440 39.748957
2 0.1 0.5 8 -2.764790 -2.692213 -2.770367 2146 4878 424 39.848941
2 0.5 0.5 8 -2.762236 -2.696362 -2.771006 2058 4720 442 39.960924
2 0.1 2 8 -2.766178 -2.690720 -2.774551 2278 5731 424 40.611825
5 0.5 2 1 -2.779705 -2.705553 -2.785201 1560 2901 360 30.044432
2 0.1 0.1 5 -2.763692 -2.687083 -2.769862 1862 3733 450 41.162742
5 0.5 0.5 1 -2.779974 -2.706102 -2.782605 1777 3467 368 30.216405
2 0.5 0.1 8 -2.761456 -2.694787 -2.771247 2090 4822 462 41.507689
2 0.5 1 8 -2.765199 -2.698666 -2.771860 2072 4763 440 42.284571
5 0.5 1 1 -2.778135 -2.706818 -2.779583 1748 3341 368 32.409072
5 0.5 0.1 1 -2.776737 -2.705491 -2.781037 1718 3276 374 31.909149
2 0.5 0.5 5 -2.763378 -2.692560 -2.774111 2245 5021 452 42.363558
2 0.1 1 1 -2.769508 -2.702853 -2.777193 2623 5132 556 67.919674
2 0.1 2 1 -2.773252 -2.700332 -2.774964 2614 5124 542 70.777239
2 0.5 2 1 -2.768015 -2.699154 -2.777804 2974 5938 538 73.566815
2 0.1 0.5 1 -2.770485 -2.699616 -2.775633 2720 5308 562 75.129577
2 0.1 0.1 1 -2.768439 -2.698846 -2.777562 2771 5256 608 83.398320
2 0.5 0.1 1 -2.762591 -2.696486 -2.780496 3427 6664 670 88.661520
2 0.5 0.5 1 -2.765368 -2.699645 -2.772477 3415 6699 636 90.168291
2 0.5 1 1 -2.765684 -2.705360 -2.780862 3281 6346 696 99.202918