In this lecture, we will take a look at the widely used Perceptron algorithm and its associated mistake bound theorem.
Lecture slides
- The Perceptron algorithm and its variants
- The Perceptron mistake bound
- Videos:
- Lecture 1, introducing the algorithm and its variants
- Lecture 2, stating and proving the Perceptron mistake bound theorem.
- Older videos: [Spring 2023, part 1], Spring 2023, part 2, Spring 2023, part 3, [fall 2018, part 1], [fall 2018, part 2],[fall 2017, part 1], [fall 2017, part 2]
Links and Resources
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Chapters 3 and 6 of Hal Daumé III, A Course in Machine Learning
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Dan Roth, On-Line Learning of Linear Functions (course notes)
Further reading
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Freund, Yoav, and Robert E. Schapire. Large margin classification using the perceptron algorithm. Machine learning 37, no. 3 (1999): 277-296.
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Roni Khardon and Gabriel Wachman, Noise Tolerant Variants of the Perceptron Algorithm, Journal of Machine Learning Research , Vol 8, pp 227–248, 2007