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# Adversarial | ||
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This repo contains code for our unsupervised domain adaptation method for relation extraction. | ||
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**Note:** Examples of the data format can be found in the data/ folder. | ||
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## Usage | ||
### Training | ||
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``` | ||
python train_final_cnn.py --num_epochs 50 --checkpoint_dir /checkpoint/dir/experiments/checkpoints/ --checkpoint_name my_checkpoint --min_df 5 --lr 0.001 --penalty 0. --adv_train_data_X /my/data/data1/all_train.txt --adv_test_data_X /my/data/biogrid_train_test/all_test.txt --test_data /my/data/test_data.txt --train_data /my/data/train_data.txt --train_data_X /my/data/data2/train.txt --val_data_X /my/data/data2/test.txt --num_iters 10000 --num_disc_updates 1 --emb_reg --adv --pos_reg --hidden_state 128 --adv --seed 42 | ||
``` | ||
usage: train_final_cnn.py [-h] [--num_epochs NUM_EPOCHS] | ||
[--hidden_state HIDDEN_STATE] | ||
[--checkpoint_dir CHECKPOINT_DIR] | ||
[--checkpoint_name CHECKPOINT_NAME] | ||
[--min_df MIN_DF] [--lr LR] [--penalty PENALTY] | ||
[--train_data_X TRAIN_DATA_X] | ||
[--train_data TRAIN_DATA] [--test_data TEST_DATA] | ||
[--val_data_X VAL_DATA_X] | ||
[--adv_train_data_X ADV_TRAIN_DATA_X] | ||
[--adv_test_data_X ADV_TEST_DATA_X] | ||
[--num_iters NUM_ITERS] [--grad_clip GRAD_CLIP] | ||
[--num_disc_updates NUM_DISC_UPDATES] [--seed SEED] | ||
[--adv] [--emb_reg] [--pos_reg] | ||
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Train Neural Network. | ||
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optional arguments: | ||
-h, --help show this help message and exit | ||
--num_epochs NUM_EPOCHS | ||
Number of updates to make. | ||
--hidden_state HIDDEN_STATE | ||
LSTM hidden state size. | ||
--checkpoint_dir CHECKPOINT_DIR | ||
Checkpoint directory. | ||
--checkpoint_name CHECKPOINT_NAME | ||
Checkpoint File Name. | ||
--min_df MIN_DF Min word count. | ||
--lr LR Learning Rate. | ||
--penalty PENALTY Regularization Parameter. | ||
--train_data_X TRAIN_DATA_X | ||
Training Data. | ||
--train_data TRAIN_DATA | ||
Training Data. | ||
--test_data TEST_DATA | ||
Training Data. | ||
--val_data_X VAL_DATA_X | ||
Validation Data. | ||
--adv_train_data_X ADV_TRAIN_DATA_X | ||
Validation Data. | ||
--adv_test_data_X ADV_TEST_DATA_X | ||
Validation Data. | ||
--num_iters NUM_ITERS | ||
Validation Data. | ||
--grad_clip GRAD_CLIP | ||
Gradient Clip Value. | ||
--num_disc_updates NUM_DISC_UPDATES | ||
Number of time to update discriminator. | ||
--seed SEED Random seed. | ||
--adv Adversarial training? | ||
--emb_reg Regularize word embeddings? | ||
--pos_reg Regularize pos embeddings? | ||
``` |
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Recent studies have provided consistent evidence that treatment with abatacept results in a rapid onset of efficacy that is maintained over the course of treatment in patients with inadequate response to DRUGB and anti- DRUGA therapies . | ||
16357751.s1 16357751 T1 T2 OTHER | ||
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DRUGA inhibitors currently under investigation include the small molecules DRUGB ( Iressa , ZDdgdgdgdg ) and erlotinib ( Tarceva , OSI-dgdgdg ) , as well as monoclonal antibodies such as cetuximab ( IMC-dgdgdg , Erbitux ) . | ||
14967461.s1 14967461 T22 T1 CLASS1 | ||
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Taken together , the results of the present study have characterized DRUGA as an inhibitor of matriptase-dg that modulates the synthesis of hepcidin and provides new insights into the regulatory mechanism of DRUGB homoeostasis , with clinical importance for a treatment of iron overload diseases . | ||
23293962.s1 23293962 T5 T1 OTHER | ||
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Taken together , the results of the present study have characterized HAI-dg as an inhibitor of matriptase-dg that modulates the synthesis of DRUGA and provides new insights into the regulatory mechanism of iron homoeostasis , with clinical importance for a treatment of DRUGB overload diseases . | ||
23293962.s1 23293962 T7 T2 OTHER | ||
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DRUGB and bromoacetylalprenololmenthane are competitive slowly reversible antagonists at the DRUGA of rat left atria . | ||
7678677.s1 7678677 T14 T19 CLASS1 | ||
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Alprenolol and DRUGB are competitive slowly reversible antagonists at the DRUGA of rat left atria . | ||
7678677.s1 7678677 T15 T19 CLASS1 | ||
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DRUGA was chemically bound via linkers to DRUGB -loaded HSA-NP . | ||
16554356.s1 16554356 T10 T3 OTHER | ||
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Apolipoprotein E was chemically bound via linkers to DRUGB -loaded DRUGA -NP . | ||
16554356.s1 16554356 T3 T11 OTHER | ||
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Discovery and optimization of DRUGB as inhibitors of methionine aminopeptidase-dg : a structural basis for the reduction of DRUGA binding . | ||
16789740.s1 16789740 T4 T13 CLASS1 | ||
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Discovery and optimization of DRUGB as inhibitors of DRUGA : a structural basis for the reduction of albumin binding . | ||
16789740.s1 16789740 T4 T14 OTHER | ||
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BACKGROUND : Since the introduction of the first DRUGA inhibitor ( ChEI ) in dgdgdgdg , most clinicians and probably most patients would consider the cholinergic drugs , DRUGB , galantamine and rivastigmine , to be the first line pharmacotherapy for mild to moderate Alzheimer 's disease.The drugs have slightly different pharmacological properties , but they all work by inhibiting the breakdown of acetylcholine , an important neurotransmitter associated with memory , by blocking the enzyme acetylcholinesterase . | ||
16437532.s1 16437532 T39 T11 CLASS1 | ||
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Mitiglinide ( DRUGB ) , a new anti-diabetic drug , is thought to stimulate insulin secretion by closing the DRUGA in pancreatic beta-cells . | ||
11716850.s1 11716850 T15 T42 CLASS1 |
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