RIT Department of Computer Science CSCI-737-01 Pattern Recognition (Spring 2017)

Instructor: Prof. Richard Zanibbi (web page; rxzvcs at rit dot edu ) Office Hrs: M 3-4pm, F 10-11am Lectures: MWF 2-2:50pm, GOL-2690

RIT Academic Calendar

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Week	Topics	Quizzes	Assign/Proj	Presentations
Classification
1	Overview, Nearest Neighbor Classification
2	Bayesian Decision Theory and Linear Classifiers	Q1
3	Decision Trees, Ensembles: AdaBoost		A1 due
4	Support Vector Machines	Q2		Class. Pres. #1
5	Ensembles: Random Forests		A2 due
6	Ensembles: Neural and 'Deep' Neural Nets	Q3		Class Pres. #2	*Wed: Career Fair
Segmentation
7	Dimensionality Reduction (PCA, LDA)		A3 due
8	[ -- Spring Break -- ]
9	Segmentation overview		Proj 1 assigned
10	Segmentation, continued	Q4		Seg. Pres #1
11	Clustering (including k-means)		Proj. 1 due
Parsing
12	Syntactic and Structural Pattern Recognition	Q5	Prof. 2 assigned	Seg. Pres #2
13	Hidden Markov Models			Parsing Pres. #1
14	Stochastic Context-Free Grammars	Q6	Proj 2 due
15	Parsing, Cont'd.		Project 3 assigned	Parsing Pres. #2
16	Project Presentations
17	-- Exam Week --		Proj 3 due

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Readings: this course makes use of a variety of texts, including Pattern Classification (Duda, Hart and Stork), Elements of Statistical Learning (Hastie, Tibshirani and Friedman), Pattern Recognition and Machine Learning (Bishop), Boosting (Freund and Schapire), C4.5 (Quinlan), along with research papers and other sources. Readings will be provided through MyCourses.