Unsupervised and Semi-supervised Learning of Structure (3/26/2020)
- Learning Features vs. Learning Structure
- Semi-supervised Learning Methods
- Unsupervised Learning Methods
- Design Decisions for Unsupervised Models
- Examples of Unsupervised Learning
- Interesting Reading (not required, no quiz) Linguistic Structure Prediction Chapter 4
- Reference: Unsupervised POS Induction w/ Word Embeddings (Lin et al. 2015)
- Reference: Unsupervised Neural Hidden Markov Models (Tran et al. 2016)
- Reference: Extracting Automata from RNNs (Giles et al. 1992)
- Reference: Normalizing Flows (Rezende and Mohamed 2015)
- Reference: HMMs with Invertible Neural Projections (He et al. 2018)
- Reference: Cross-lingual Syntactic Transfer (He et al. 2019)
- Reference: Gated Convolution (Cho et al. 2014)
- Reference: Learning Grammar with RL (Yogatama et al. 2016)
- Reference: Learning to Compose Task-specific Tree Structures (Choi et al. 2017)
- Reference: Parsing w/ a Semantic Objective (Williams et al. 2017)
- Reference: What do RNN Grammars Learn About Syntax? (Kuncoro et al. 2017)
- Reference: Do Latent Tree Learning Models Learn Meaningful Structure? (Williams et al. 2018)
- Reference: Dependency Model with Valence (Klein and Manning 2004)
- Reference: Unsupervised Neural Dependency Parsing (Jiang et al. 2016)
- Reference: CRF Autoencoders for Unsuprevised Dependency Parsing (Cai et al. 2017)
- Reference: Learning Language-level Features (Malaviya et al. 2017)
- Reference: Embedded Segmental k-means Models (Kamper et al. 2017)
- Reference: Speech Segmentation (Elsner and Shain 2017)
- Reference: Word Discovery w/ Encoder-decoder Models (Boito et al. 2017)