54 citations · 73 across the 5 of their papers we have counts for
7 papers · 1 filter
Learning to Teach with Dynamic Loss Functions
Lijun Wu, Fei Tian, Yingce Xia +4
Teaching is critical to human society: it is with teaching that prospective students are educated and human civilization can be inherited and advanced. A good teacher not only prov…
A Study of Reinforcement Learning for Neural Machine Translation
Lijun Wu, Fei Tian, Tao Qin +2
Recent studies have shown that reinforcement learning (RL) is an effective approach for improving the performance of neural machine translation (NMT) system. However, due to its in…
Neural Architecture Optimization
Renqian Luo, Fei Tian, Tao Qin +2
Automatic neural architecture design has shown its potential in discovering powerful neural network architectures. Existing methods, no matter based on reinforcement learning or ev…
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li, Di He, Fei Tian +4
Long Short-Term Memory (LSTM) is one of the most widely used recurrent structures in sequence modeling. It aims to use gates to control information flow (e.g., whether to skip some…
Learning to Teach
Yang Fan, Fei Tian, Tao Qin +2
Teaching plays a very important role in our society, by spreading human knowledge and educating our next generations. A good teacher will select appropriate teaching materials, imp…
Learning What Data to Learn
Yang Fan, Fei Tian, Tao Qin +2
Machine learning is essentially the sciences of playing with data. An adaptive data selection strategy, enabling to dynamically choose different data at various training stages, ca…