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1. 10-601B Generalization and Overfitting: Sample Complexity Results for Supervised Classification 3 →‎ 10-601B Model Selection
2. 10-601B Intro to neural Networks →‎ 10-601B Intro to Neural Networks
3. 10-601B Perceptrons and SVMs →‎ 10-601B Perceptrons and Large Margin
4. 10-601 K-NN And Trees →‎ 10-601 K-NN And Trees - Lecture from Fall 2013
5. 10-605 in Spring 2014 →‎ Machine Learning with Large Datasets 10-605 in Spring 2014
6. 10-605 in Spring 2015 →‎ Machine Learning with Large Datasets 10-605 in Spring 2015
7. A high-performance semi-supervised learning method for text chunking →‎ Ando & Zhang, 2005, A high-performance semi-supervised learning method for text chunking
8. Also - a draft schedule for 10-601B →‎ Draft schedule for 10-601B in Spring 2016
9. AlternatingMinimization →‎ Alternating Minimization
10. Analysis of Social Media Spring, 2011 →‎ User:Manajs/Analysis of Social Media Spring, 2011
11. Ando & Zhang, 2005, A high-performance semi-supervised learning method for text chunking →‎ R. K. Ando and T. Zhang. ACL 2005
12. Ando and Zhang ACL 2005 →‎ A high-performance semi-supervised learning method for text chunking
13. Attribute extraction →‎ Attribute Extraction
14. Autolab guide for ta →‎ Autolab Guide for TA
15. Automatically Refining the Wikipedia Infobox Ontology →‎ Wu and Weld ACM 2008
16. Baum-Welch →‎ Forward-Backward
17. BeliefPropagation →‎ Belief Propagation
18. Berg-Kirkpatrick, ACL 2010: Painless Unsupervised Learning with Features →‎ Berg-Kirkpatrick et al, ACL 2010: Painless Unsupervised Learning with Features
19. Berg-Kirkpatrick, HLT 2010: Painless Unsupervised Learning with Features →‎ Berg-Kirkpatrick, ACL 2010: Painless Unsupervised Learning with Features
20. CRF →‎ Conditional Random Fields

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