Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2015

This is the syllabus for Machine Learning with Large Datasets 10-605 in Spring 2015.

Notes:

• The assignments posted are drafts based on the assignments from 2014, and will be modified over the course of the semester - some may be changed substantially.
• Lecture notes and/or slides will be (re)posted around the time of the lectures.

January

• Tues Jan 13. Overview of course, cost of various operations, asymptotic analysis.
• Thus Jan 15. Review of probabilities, joint distributions and naive Bayes
  • HW1A: streaming Naive Bayes 1 (with feature counts in memory). PDF Handout
• Tues Jan 20. Streaming algorithms and Naive Bayes; The stream-and-sort design pattern; Naive Bayes for large feature sets.
  • HW1B: streaming Naive Bayes 2 (with feature counts on disk) with stream-and-sort. PDF Handout
  • For 10/11-805 students: a one-paragraph summary of a recent research result you'd like to present is due. If you're planning/hoping to transfer from 605, but haven't yet transferred, then also submit this assignment. Email to wcohen+805 AT gmail.com with the subject "Presentation" and include, in addition to your summary:
    • Your name and andrew id
    • A link to the paper
    • Your best guess as to what lectures should precede the presentation
    • Due by 11:59:59pm EST Tuesday.
• Thus Jan 22. Messages, records and workflows; Phrase finding.
• Tues Jan 27. Messages, records and workflows; Rocchio
  • HW1A and HW1B due.
  • HW2: phrase finding with stream-and-sort. PDF Handout (DRAFT)
• Thus Jan 29. Hadoop and Workflows

February

• Tues Feb 3. Perceptrons/Map-reduce and Hadoop.
• Thus Feb 5. Parallel Perceptrons.
• Tues Feb 10. student presentations
  • HW2 due: phrase finding with stream-and-sort
  • HW3,4: Naive Bayes with Streaming Hadoop, Naive Bayes with Hadoop & Phrase-finding with Hadoop. PDF Handouts: HW3 - warmup,HW3,HW4.
• Thus Feb 12. student presentations
• Tues Feb 17. Scalable SGD and Hash Kernels
  • For 10/11-805 students: initial draft of project proposal is due.
• Thus Feb 19. Matrix Factorization and SGD
• Tues Feb 24. SGD for Matrix Factorization, and Randomized Algorithms 1 (Bloom Filters)
  • HW3 due: Naive Bayes with Hadoop
• Thus Feb 26. Randomized Algorithms

March

• Tues Mar 3. student presentations
• Thus Mar 5. student presentations
  • HW4 due: Phrase-finding with Hadoop
  • HW5: memory-efficient SGD PDF handout
  • For 10/11-805 students: project proposal is due. This must contain a complete description of the data you will use.
• Tues Mar 10. no class - spring break.
• Thus Mar 12. no class - spring break.
• Tues Mar 17. Scalable PageRank
  • HW5 due: memory-efficient SGD
  • HW6: Subsampling and visualizing a graph. PDF handout
• Thus Mar 19. Subsampling a graph with RWR
• Tues Mar 24. Subsamping continued and SSL on Graphs AAAI Spring Symposium week
• Thus Mar 26. Scalable spectral clustering techniques. AAAI Spring Symposium week
• Tues Mar 31. Sparse sampling and parallelization for LDA
  • HW6 due: Subsampling and visualizing a graph.
  • HW7: TBA

April and May

• Thus Apr 2. Speeding up LDA-like models: All-reduce and online LDA
• Tues Apr 7. student presentations
• Thus Apr 9. student presentations
• Tues Apr 14. Scalable Similarity Joins
  • HW7 due
  • HW8: TBA
• Thus Apr 16. no class : carnival
• Tues Apr 21. Graph models for large-scale ML
• Thus Apr 23. Poster session for 10/11-805 projects
• Tues Apr 28. Exam review session.
  • HW8: due
  • PDF practice questions
  • Review session slides
• Thus Apr 30. In-class exam.

• Tues May 5.
  • For 10/11-805 students: project reports are due

Topics covered in previous years but not in 2015

• Workflows in PIG
• Fast KNN and similarity joins
• First-order logics
• Scalable First-order logics