Time: June 4, 4:25-5:25pm
In the spirit of a workshop, we are planning an informal panel discussion. The goal is to get together and figure out what important issues in SSL-NLP need more attention, what lessons should be shared, etc. The material here is still tentative and subject to change. Please let us know (email email@example.com) if you have any suggestions!
- Hal Daume (University of Utah)
- Andrew Goldberg (University of Wisconsin - Madison)
- David McClotsky (Brown University)
Invited Position Paper:
- Sajib Dasgupta and Vincent Ng (UT Dallas). Discriminative Models for Semi-supervised Natural Language Learning
- Hal Daume (U of Utah). Semi-supervised or Semi-unsupervised?
- Should there be a shared task for SSL-NLP, and if so, how should the data and evaluation be set up?
- What do you think are the open problems in semi-supervised learning for NLP? What should researchers focus on?
- Are there any emerging applications where SSL-NLP will be an important enabler?
- Human language learning and semi-supervised learning -- what are the connections that are worth investigating?
- Online learning and lifelong learning.