Whether you get liposuction or tummy tuck surgery done, you need to remain healthy. Going back to poor eating habits and a sedentary lifestyle after surgery can lead to gaining the weight back. You should be regularly exercising to build muscle and burn off excess calories throughout the day.
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Discussion in '2nd Gen. Builds (2005-2015)' started by starforsaken, Oct 9, 2016.
Products Discussed in
TuckER: Tensor Factorization for Knowledge Graph Completion
This codebase contains PyTorch implementation of the paper:
TuckER: Tensor Factorization for Knowledge Graph Completion.Ivana Balažević, Carl Allen, and Timothy M. Hospedales.Empirical Methods in Natural Language Processing (EMNLP), 2019.[Paper]
TuckER: Tensor Factorization for Knowledge Graph Completion.Ivana Balažević, Carl Allen, and Timothy M. Hospedales.ICML Adaptive & Multitask Learning Workshop, 2019.[Short Paper]
Link Prediction Results
Dataset | MRR | Hits@10 | Hits@3 | Hits@1 |
---|---|---|---|---|
FB15k | 0.795 | 0.892 | 0.833 | 0.741 |
WN18 | 0.953 | 0.958 | 0.955 | 0.949 |
FB15k-237 | 0.358 | 0.544 | 0.394 | 0.266 |
WN18RR | 0.470 | 0.526 | 0.482 | 0.443 |
Running a model
To run the model, execute the following command:
Available datasets are:
To reproduce the results from the paper, use the following combinations of hyperparameters with batch_size=128
:
dataset | lr | dr | edim | rdim | input_d | hidden_d1 | hidden_d2 | label_smoothing |
---|---|---|---|---|---|---|---|---|
FB15k | 0.003 | 0.99 | 200 | 200 | 0.2 | 0.2 | 0.3 | 0. |
WN18 | 0.005 | 0.995 | 200 | 30 | 0.2 | 0.1 | 0.2 | 0.1 |
FB15k-237 | 0.0005 | 1.0 | 200 | 200 | 0.3 | 0.4 | 0.5 | 0.1 |
WN18RR | 0.003 | 1.0 | 200 | 30 | 0.2 | 0.2 | 0.3 | 0.1 |
Requirements
Tuck 1.0 Build 21 Inch
The codebase is implemented in Python 3.6.6. Required packages are:
Tuck 1.0 Build 21 Free
Citation
Tuck 1.0 Build 21 Full
If you found this codebase useful, please cite: