Runzhe Yang

Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning

2017

Hand-crafted rules and reinforcement learning (RL) are two popular choices to obtain dialogue policy. The rule-based policy is often reliable within predefined scope but not self-adaptable, whereas RL is evolvable with data but often suffers …

End-to-End Refinement Guided by Pre-trained Prototypical Classifier

2018 · arXiv (Cornell University)

Many real-world tasks involve identifying patterns from data satisfying background or prior knowledge. In domains like materials discovery, due to the flaws and biases in raw experimental data, the identification of X-ray diffraction patterns (XRD) …