NLP Status Report 2016-11-21

Date	People	Last Week	This Week
2016/11/21	Yang Feng	rnng+mn 1) ran experiments of rnng+mn [report] ; 2) used top-k for memory, under training sequence-to-sequence + mn 1) wrote the proposal 2) discussed the details with Andy intern interview Huilan's work	rnng+mn 1) get the result of top-k; 2) try bigger memory; sequence-to-sequence + mn 1)coding work Huilan's work 1) try syntax-based TM
	Jiyuan Zhang	ran decoder-memory model, but the effect is not obvious changed binding way of memory and atten models, can generate different style of poetry cleanned up my code wrote a techreport about poemGen [1] submitted two databases about poemGen and musicGen	explored a variety of binding ways of memory and atten model
	Andi Zhang	prepare new data set for paraphrase, wiped out repetition & most of the noises run NMT on fr-en data set and new paraphrase set read through source code to find ways to modify it helped Guli with running NMT on our server	decide to drop theano or not start to work on codes
	Shiyue Zhang	run rnng on MKL successfully, which can double or triple the speed. Revised the RNNG User Guide. rerun the original model and get the final result 92.32 rerun the wrong memory models, still running implement the dynamic memory model and get the result 92.54 which is 0.22 better than baseline try another structure of memory [report]	try more different models and summary the results publish the technical reports
	Guli	read the paper "NMT by jointly learning to align and translate" read the codes of paper and ran NMT (cs-en) on GPU with the help of Andi learn more about python prepare data for Ontology Library	continue to prepare the data follow the teacher Yang's instructions