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Commits on Apr 5, 2018
Update README.md
Davis Liang
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Accepted paper to IJCNLP 2017.
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Commits on May 3, 2017
Merge pull request #9 from anapetrova/tensorboard
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Commits on Apr 18, 2017
refactoring
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Finalized all code MRNN and CRNN for all datasets
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Commits on Apr 17, 2017
Update README.md
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Commits on Apr 10, 2017
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Commits on Apr 9, 2017
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Commits on Apr 7, 2017
Update README.md
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Commits on Apr 6, 2017
MRNN complete
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Commits on Apr 5, 2017
mrnn updated with annealing + more epochs and converges to better place
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Commits on Apr 2, 2017
working mcrnn_model
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Commits on Apr 1, 2017
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added hyperparam search code
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crnn model for missing word and word generation
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Commits on Mar 31, 2017
progress on mrnn with automated task next word prediction
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Tensorboard added to mcrnn.py
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Commits on Mar 30, 2017
starting to write data preprocessing and models for state of the art experiments on RTMR and 20NG
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Commits on Mar 17, 2017
added batchnorm
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Commits on Mar 14, 2017
fixed ccrnn code.
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mcrnn complete with lstm in branching decoders. ccrnn implementation begun, some bugs to fix. t2c implementation also includes second lstm layer to match contextual rnn models.
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Commits on Mar 11, 2017
finalized multitasking contextual RNN. Our results show that this RNN converges to a better minima than a normal LSTM (with same number of parameters in the 'task' stream) by ~5%
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Commits on Mar 10, 2017
finished verifying mtl code... kinda weird it gets up to 74% and rising performance
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Commits on Mar 8, 2017
checkpoint: some changese to MTL model for multitasking
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started some new code for context-driven MTL models
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Commits on Mar 6, 2017
Update README.md
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Update pom.xml
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Update README.md
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Commits on Mar 3, 2017
Merge pull request #7 from anapetrova/kafka
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Commits on Mar 2, 2017
Updated starting script to include Kafka server launch
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Updated POM file to include Kafka dependencies
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Commits on Feb 23, 2017
Merge branch 'master' of github.com:davisliang/tweetnet
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added more fun stuff
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Commits on Feb 19, 2017
updated gitignore to ignore log files
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created dataset normalizer, and new clstm model. contextual model performs at around 92% accuracy for 71 topic classes. Created a few other models including c2c and t2c. Updated gitignore to ignore…
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Davis Liang
