Difference between revisions of "Syllabus for Structured Prediction 10-710 in Fall 2011"
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* Tues 8/30. [[Class Meeting for 10-710 08-30-2011|Introduction/Overview]] (Noah) | * Tues 8/30. [[Class Meeting for 10-710 08-30-2011|Introduction/Overview]] (Noah) | ||
* Thus 9/1. [[Class Meeting for 10-710 09-01-2011|HMMs as structured-output prediction models]]. (William) | * Thus 9/1. [[Class Meeting for 10-710 09-01-2011|HMMs as structured-output prediction models]]. (William) | ||
| − | * Tues 9/6. HMMs to MEMMs. (William) | + | * Tues 9/6. [[Class Meeting for 10-710 09-06-2011|HMMs to MEMMs]]. (William) |
* Thus 9/8. [[Class Meeting for 10-710 09-08-2011|CRFs]]. (William). | * Thus 9/8. [[Class Meeting for 10-710 09-08-2011|CRFs]]. (William). | ||
* Tues 9/13. [[Class Meeting for 10-710 09-13-2011|Pseudo-likelihood inference]]. (William). | * Tues 9/13. [[Class Meeting for 10-710 09-13-2011|Pseudo-likelihood inference]]. (William). | ||
Revision as of 10:17, 6 September 2011
This is the syllabus for Structured Prediction 10-710 in Fall 2011. The slides available may be out of date (from the last version of the class) but will be updated after each lecture.
Contents
August/September
- Tues 8/30. Introduction/Overview (Noah)
- Thus 9/1. HMMs as structured-output prediction models. (William)
- Tues 9/6. HMMs to MEMMs. (William)
- Thus 9/8. CRFs. (William).
- Tues 9/13. Pseudo-likelihood inference. (William).
- Thus 9/15. Conditional structure, conditional estimation. (Noah).
- Tues 9/20. Perceptrons and margin-based learning. (William).
- Thus 9/22. Ranking perceptrons and margin-based learning. (William).
- Tues 9/27. Stacking, Searn, and related "meta-learning" techniques. (William).
- Thus 9/29. Generalizing SVM to structures. (Noah; note this is Rosh Hashanah)
October
- Thus 10/4. Dynamic programming techniques (Noah).
- Tues 10/6. Inference with ILP and other methods (Noah).
- Tues 10/11. PCFGs and parsing (Noah).
- Thus 10/13. Spanning trees and dependency parsing. (Noah).
- Tues 10/18. Kernels for structured inputs. (William).
- Thus 10/20. Kernels for structured outputs. (Noah).
- Tues 10/25. Mid-term project reports - short presentations of task, dataset, and baseline.
- Thus 10/27. Learning edit distances. (William).
November
- Tues 11/1. Weighted FSTs. (Noah).
- Thus 11/3. Non-monotonic alignment for translation problems. (Noah).
- Tues 11/8. EM for sequences. (William).
- Thus 11/10. EM for trees. (Noah).
- Tues 11/15. Discriminative latent-variable models. (Noah).
- Thus 11/17. Posterior regularization and other EM variants. (Noah).
- Tues 11/22. Regularizers derived from unannotated data. (William).
- Thus 11/24 -- Thanksgiving, no class
- Tues 11/29. Classification on graphs (William).
December
- Thus 12/1. Bayesian approaches to structured models (Noah).
- Tues 12/6. Project presentations 1
- Thus 12/8. Project presentations 2.
- Mon 12/12. Final projects due.
