CSCI-737: Pattern Recognition (Spring 2017)

  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

News --- Schedule --- Syllabus --- Resources --- MyCourses


Week 15

  • **Please complete the online course evaluation.** Comments from students in previous years have been very important for improving the course from year-to-year. I'd be grateful if you could identify both things that you feel worked and should be kept in the course, as well as parts of the course that you feel could be changed or improved.
  • Office Hours on Friday, and during Exam Week: due to a conflict, office hours will be held Friday from 3-4pm. I am happy to also meet with students next week by appointment from Monday through Thursday.
  • The final set of paper presentations will be given in-class on Monday.
  • Teams will present their projects 1-2 and plans for project 3 in-class on Wednesday and Friday (requirements are available through MyCourses). We will set the schedule in-class on Monday.
  • Project 3 is due Sunday, May 21st; after 11:59pm on Monday May 22nd, I will not accept project submissions due to grading deadlines.

Week 14

  • Deadline Extension: Project 2 is due Friday at 11:59pm.
  • Papers on parsing math notation will be presented on Wednesday.
  • The last set of paper presentations will be given next Monday; papers and a doodle poll to select papers will be posted by Monday evening.
  • Project Presentations: groups will present a summary of their projects in-class next Wednesday and Friday. Instructions with be posted on MyCourses Monday evening.
  • Project 3 (on parsing handwritten math) will be given out on Thursday, and due two weeks later (Thursday of Exam week).
  • We will talk about hidden Markov Models and Stochastic Context-Free Grammars this week, as well as the projects.

Week 13

  • We will have our second round of segmentation papers (concerning math notation) on Monday.
  • Project 2 is due Monday, May 1st at 11:59pm.
  • Slides on clustering and Hidden Markov Models have been posted on MyCourses.

Week 12

  • Papers on segmenting symbols have been posted; presentations will be in-class next Monday. The doodle poll is here.
  • Project 1 is due Monday of Week 14.
  • The next round of papers for presentation (on parsing math notation) will be posted this coming Monday.

Week 11

  • Read the paper on segmentation by Casey and Lecolinet.
  • Project 2 will be given out on Friday.

Week 10

  • Project 1 is due Sunday April 9th at 11:59pm. The test symbol set has been posted as '' under 'Projects -> Project 1: Classification' on MyCourses.
  • Read the paper on segmentation by Casey and Lecolinet. The paper is available through MyCourses.
  • We will finish up our discussion of LDA/PCA and begin covering segmentation this week.
  • Resources related to deep and/or convolutional neural network models and libraries have been posted on MyCourses, under 'References.'

Week 9

  • There will be a quiz at the beginning of class on Monday.
  • **Extension:** Papers for presentation this Friday will be presented in-class on Monday of Week 10. For groups presenting, please fill out this Doodle Poll to select papers ASAP: paper selection doodle poll.
  • Assignment 3 is due on Wednesday at 11:59pm.
  • Project 1 is due Sunday April 9th at 11:59pm.
  • My office hours on Monday from 3:30-4 will be taken up with a meeting, unfortunately. Please feel free to stop by during my office hours on Friday (10-10:50am) or send email if this causes any difficulties for you.

Week 8

  • Assignment 3 is due next Wednesday at 11:59pm.
  • Project 1 has been posted on MyCourses, and is due Sunday April 9 at 11:59pm. The project will be completed by groups of two students.
  • Read Sections 2.3.5 - 3.3 of the Criminisi paper on Random Forests (available through MyCourses, under 'References).
  • The first round of Segmentation papers will be presented next Friday. Students from the last round of paper presentations will be presenting again (TPAMI papers, this time).
  • Project 1 will be assigned on Friday.
  • Class on Friday will start 5-10 minutes late, due to the visiting speaker (Jeremy Pickens, Catalyst).

Week 7

  • Project 1 (symbol classification) will be posted after the break.
  • Slides on Support Vector Machines (SVMs) have been posted. We will discuss these later this week. A related reading from Bishop's "Pattern Recognition and Machine Learning" has also been posted (this is optional).

Week 6

  • Extension: Assignment 2 is due Monday at 11:59pm.
  • Research Paper Presentations: research papers for presentation are now on MyCourses. The sign-up page to select papers is online here: doodle pool. Paper presentations will be given in-class next Wednesday.
  • Reading: Read Chs. 1 and 3.4 from Boosting (available online through MyCourses)
  • Slides from the first round of paper presentations have been posted on MyCourses.

Week 5

  • There will be a quiz in-class on Monday.
  • Readings on decision trees (C4.5) have been posted on MyCourses. Please read these before class on Monday.
  • Research papers for the 2nd group of presenters will be posted Friday, with presentations next Friday (Wk 6).
  • Career Fair: Next Wednesday is the career fair; students who miss class will be responsible for missed material.

Week 4

  • There will be a quiz on Monday.
  • Assignment 2 has been posted on MyCourses. It is due Saturday Feb. 25th by 11:59pm.
  • Our first research paper presentations will be given in-class on Wednesday. We will have one of these presentations in-class on Wednesday next week.
  • There will be no class on Friday - please stop by the RIT AI retreat instead! (link).

Week 3

  • Assignment 1 is due Saturday at 11:59pm (through MyCourses).
  • Computer Science Department Scholarships and Awards are available. Please apply online here by March 10th.
  • Read Section 2.1 of 'Bayes-DuinCh2' under 'References' on MyCourses before class on Wednesday.
  • We will have four paper presentations next Wednesday. The presenting groups are: Brody and Poppy, Nihar and Aravindh, Aditya and Paridhi, and Ritvik and Rahul. The doodle poll to select papers is located here.
  • On Wednedsay we will start discussing Bayesian Decision theory.
  • Class is cancelled next Friday (Wk 4), due to the day-long AI Retreat.

Week 2

  • Assignment 1 has been posted. It is due one week Saturday Feb. 11th at 11:59pm (through MyCourses).
  • Next week we will start making plans for our first round of research paper presentations, on classification.
  • There will *not* be a quiz on Monday.
  • Next week we will choose the first four groups of two who will present papers on Friday of Week 4.

Week 1

  • Read Chs. 1 and 2.1-2.4 in "The Elements of Statistical Learning" before class on Friday on classification, and classifiers based on nearest-neighbors and least-squares. The book is available through a link in MyCourses (go to Content -> References).
  • The first quiz will be given next Monday (Week 2).
  • Assignment 1 will be given out next Friday (Week 2).
  • Lecture slides, assignments, and projects will be posted on MyCourses.