Difference between revisions of "Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2015"

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** Each '''student working on a project''' should send to wcohen+805@gmail.com an update, between 1/2 page and 1 page long, saying what concrete tasks you've accomplished to date, how these tasks are part of the overall project (if you're not the only member), and what you plan to do between 4/13 and the presentation on 4/23.   
 
** Each '''student working on a project''' should send to wcohen+805@gmail.com an update, between 1/2 page and 1 page long, saying what concrete tasks you've accomplished to date, how these tasks are part of the overall project (if you're not the only member), and what you plan to do between 4/13 and the presentation on 4/23.   
 
** Additionally, each '''project lead''' (i.e., each 805 student that has any 10-605 student working with them) should add a list of who's working on their project, and one line indicating if they're making good progress so far.
 
** Additionally, each '''project lead''' (i.e., each 805 student that has any 10-605 student working with them) should add a list of who's working on their project, and one line indicating if they're making good progress so far.
* Tues Apr 14.  [[Class_meeting_for_10-605_GraphLab|Graph-based ML paradigms]]
+
* Tues Apr 14.  TBA
 
** '''HW7 due'''
 
** '''HW7 due'''
 
** ''HW8: Using parameter servers''
 
** ''HW8: Using parameter servers''

Revision as of 18:11, 9 April 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

February

March

  • Sun Mar 1.
    • HW3 due: Naive Bayes with Hadoop MapReduce
  • Tues Mar 3. student presentations
    • Adams Wei Yu (weiyu at andrew): fast PPR on Map-Reduce [1]
    • Jakub Pachocki: factorization machines (and hash kernels?) [2]
    • Wanli Ma (wanlim at andrew): coresets for k-segmentation of streams
  • Thus Mar 5. student presentations
    • Quiz: [3]
    • Matt Gardner (mg1 at cs): Large-scale extensions of the path ranking algorithm [4]
    • Jesse Dodge (jessed at andrew): large-scale lasso regularization [5]
    • Ishan Misra (imisra at andrew): LSH for object detection [6]
    • 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.
  • Sat Mar 7 (extended from Friday):
    • HW4 due: Phrase-finding with Hadoop
  • Tues Mar 10. no class - spring break.
  • Thus Mar 12. no class - spring break.
  • Tues Mar 17. Scalable PageRank PDF handout
  • Thus Mar 19. Subsampling a graph with RWR
    • HW5 due: memory-efficient SGD
    • HW6: Subsampling and visualizing a graph.' PDF handout'
  • Tues Mar 24.
    • Student presentation: Rohan Ramanath, Bayesian Optimization
    • Guest lecture: Dai Wei, CMU, Parameter servers. (Note: This will be very relevant for one of the later HWs).
  • Thus Mar 26. Guest lecture: D. Sculley, Google, TBA
  • Tues Mar 31. Sparse sampling and parallelization for LDA

April and May

  • Wed April 1
    • HW6 due: Subsampling and visualizing a graph.
    • HW7: Matrix Factorization in Spark HW7 PDF Handout
  • Thus Apr 2. Speeding up LDA-like models: All-reduce and online LDA
  • Tues Apr 7. Guest lecture - Alex Beutel, SGD for Tensors
  • Thus Apr 9. Guest lecture - Alex Smola, Scalable parameter servers
  • Mon Apr 13. Informal update due for students working on project teams due.
    • Each student working on a project should send to wcohen+805@gmail.com an update, between 1/2 page and 1 page long, saying what concrete tasks you've accomplished to date, how these tasks are part of the overall project (if you're not the only member), and what you plan to do between 4/13 and the presentation on 4/23.
    • Additionally, each project lead (i.e., each 805 student that has any 10-605 student working with them) should add a list of who's working on their project, and one line indicating if they're making good progress so far.
  • Tues Apr 14. TBA
    • HW7 due
    • HW8: Using parameter servers
  • Thus Apr 16. no class : carnival
  • Tues Apr 21. Graph models for large-scale ML
  • Thus Apr 23. Presentation for 10/11-805 projects
  • Tues Apr 28. Exam review session.
  • 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