报告题目：Bidirectional Attentional Encoder-Decoder and Bidirectional Beam Search
报 告 人：Kamal Al-Sabahi(扎伊德), 16级留学博士，亚博取款心丈秒到账，亚博取款心丈秒到账
Sequence generative models with RNN variants, such as LSTM, GRU, show promising results. However, they still have some issues that limit their performance, especially while dealing with long sequences. One of the issues is that all current models employ a unidirectional decoder, which reasons only about the past and still limited to retain future context while giving a prediction. This makes these models suffer on their own by generating unbalanced outputs. To this end, bidirectional encoder-decoder architecture is used to tackle the aforementioned issues. Moreover, a bidirectional beam search mechanism is used to make inference from the bidirectional model.