030e40e
(define_task)
tuning for clustering by lstm and data_batching_new (make clustering module depart from prediction network) by
2022-04-14 18:32:16 +0430
c701e2c
only consider positive interaction for task embedding by
2022-04-12 19:37:01 +0430
5273533
Revert "deep kmeans loss" by
2022-04-10 19:31:50 +0430
07bb1cd
check result of hyper tuning (best_result1) by
2022-04-10 14:44:50 +0430
3a3b256
Revert "prepare for hyper parameter tuning" by
2022-04-10 02:57:13 +0430
b4d130e
deep kmeans loss by
2022-04-08 17:43:09 +0430
dc38c40
tanp loss (kl loss) by
2022-04-08 02:59:54 +0430
acacb68
tanp loss (kl loss) by
2022-04-07 23:52:42 +0430
d425ba0
cluster loss (try to hard assignment) by
2022-04-07 19:54:03 +0430
576c0e9
prepare for hyper parameter tuning by
2022-04-05 00:24:52 +0430
d2d5563
prepare for hyper parameter tuning by
2022-04-01 18:36:16 +0430
dda2618
solve gamma and beta problem by
2022-03-31 08:09:39 +0430
908149d
task encoder consider item's score there is problems that should set inner loop larger than one by
2022-03-30 10:36:30 +0430
d9e027a
user clustering effects prediction network's weights by
2022-03-29 02:22:55 +0430
34018e3
prepare for the branch by
2022-03-28 16:42:22 +0430
01b24e1
(HEAD -> master)
generic algorithms and parameters by
2021-09-21 07:07:13 +0430
a23a4ec
generic algorithms and parameters by
2021-09-09 09:27:58 +0430
a9d1772
other hyper parameters by
2021-09-08 17:52:27 +0430
153f3b9
prepare to run on a cpu by
2021-09-08 01:16:29 +0430
a4e913f
GBML + some optimization for cuda memory by
2021-09-08 00:58:21 +0430
0d298f3
melu by l2l + MetaSGD + second oreder by
2021-09-06 21:09:34 +0430
14e32e0
melu by l2l + MetaSGD by
2021-09-06 04:31:02 +0430
2ff9d9e
melu by l2l + MetaSGD by
2021-09-06 04:24:48 +0430
00555ed
melu by l2l + MetaSGD by
2021-09-06 04:15:21 +0430