CMU Neural Nets for NLP 2017 - Advanced Search Algorithms
Offered By: Graham Neubig via YouTube
Course Description
Overview
Syllabus
Intro
Potential Problems
Dealing with disparity in actions Effective Inference for Generative Neural Parsing (Mitchell Stern et al., 2017)
Threshold based pruning 'Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation' (Y Wu et al. 2016)
More complicated normalization Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation' (Y Wu et al. 2016)
Beam Search-Benefits and Drawbacks
More beam search in training A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models (Goyal et al., 2017)
Classical A* parsing al., 2003
Is the heuristic admissible? Global Neural CCG Parsing with Optimality Guarantees (Lee et al. 2016)
Estimating future costs Learning to Decode for Future Success (Li et al., 2017)
Monte-Carlo Tree Search Human-like Natural Language Generation Using
Taught by
Graham Neubig
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