Difference between revisions of "Class meeting for 10-405 Parallel Perceptrons"
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=== Things to Remember === | === Things to Remember === | ||
| + | |||
| + | * Definition of mistake bound | ||
| + | * Definition of perceptron algorithm | ||
| + | ** Mistake bound analysis for perceptrons, in terms of margin and example radius | ||
| + | * Converting perceptrons to batch: voted perceptron, averaged perceptron | ||
| + | * Definition of the ranking perceptron and kernel perceptron | ||
Revision as of 12:36, 5 March 2018
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-405 in Spring 2018.
Slides
- Lecture 1: in Powerpoint, in PDF.
- Lecture 2: in Powerpoint, in PDF.
- Lecture 3: : in Powerpoint, in PDF.
Quiz
Readings
Readings
- Large Margin Classification Using the Perceptron Algorithm, Freund and Schapire, MLJ 1999
- Discriminative Training Methods for Hidden Markov Models, Collins EMNLP 2002.
- Distributed Training Strategies for the Structured Perceptron, R. McDonald, K. Hall and G. Mann, North American Association for Computational Linguistics (NAACL), 2010.
Things to Remember
- Definition of mistake bound
- Definition of perceptron algorithm
- Mistake bound analysis for perceptrons, in terms of margin and example radius
- Converting perceptrons to batch: voted perceptron, averaged perceptron
- Definition of the ranking perceptron and kernel perceptron
