“Tianyi Luo 2016-04-25”版本间的差异

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* Speed up process of the test performance about theano version of Generationg the similar questions' vectors based on RNN.
 
* Speed up process of the test performance about theano version of Generationg the similar questions' vectors based on RNN.
 
--------------------2016-04-23
 
--------------------2016-04-23
* Use entity match rules(dpk, ix, lpk sv + machine number) to improve the accuracy from 38% to 58%.
+
* Use entity match rule 1(dpk, ix, lpk sv + machine number) to improve the accuracy from 38% to 58%.
 
--------------------2016-04-24
 
--------------------2016-04-24
* Use entity match rules(dps, s, e, fp, tps, q, 200 + machine number and machine number only) to improve the accuracy from 58% to 72%.
+
* Use entity match rules 2+3(dps, s, e, fp, tps, q, 200 + machine number and machine number only) to improve the accuracy from 58% to 72%.
 +
* Use entity match rules 4(dpk, ix, lpk sv, dps, s, e, fp, tps, q + machine number + English chacracters) to improve the accuracy from 58% to 72%.
 
=== Plan to do next week ===
 
=== Plan to do next week ===
 
* To implement tensorflow version of RNN/LSTM Max margin vector training.
 
* To implement tensorflow version of RNN/LSTM Max margin vector training.

2016年4月24日 (日) 14:12的版本

Plan to do this week

  • To implement tensorflow version of RNN/LSTM Max margin vector training.

Work done in this week


2016-04-18
  • Optimize theano version of Generationg the similar questions' vectors based on RNN.
  • Finish implementing theano version of LSTM Max margin vector training.

2016-04-19
  • Optimize theano version of Generationg the similar questions' vectors based on RNN.

2016-04-20
  • Finish submiting the camera version paper of IJCAI 2016.
  • Update the version of Technical Report about Chinese Song Iambics generation.

2016-04-21
  • Finish helping Teacher Wang to prepare for text group's presentation(Tang poetry and Songci generation and Intelligent QA system) for Tsinghua University's 105 anniversary.
  • Submit our IJCAI paper to arxiv. (Solve a big problem about submitting the paper including Chinese chacracters. Solution)
  • Optimize theano version of Generationg the similar questions' vectors based on RNN.

2016-04-22
  • Speed up process of the test performance about theano version of Generationg the similar questions' vectors based on RNN.

2016-04-23
  • Use entity match rule 1(dpk, ix, lpk sv + machine number) to improve the accuracy from 38% to 58%.

2016-04-24
  • Use entity match rules 2+3(dps, s, e, fp, tps, q, 200 + machine number and machine number only) to improve the accuracy from 58% to 72%.
  • Use entity match rules 4(dpk, ix, lpk sv, dps, s, e, fp, tps, q + machine number + English chacracters) to improve the accuracy from 58% to 72%.

Plan to do next week

  • To implement tensorflow version of RNN/LSTM Max margin vector training.
  • To implement attention chatting model with xiaobing corpus.

Interested papers

  • Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [pdf]