CPSC 633-600 Read-Only Bulletin Board

Last modified: 1/22/09, 03:46PM (Thu)

This page will have all relevant email transactions with the students regarding the AI course, so that everyone has equal information regarding the course material.

Newest transactions will be posted on the top. Regularly view this page to see what's going on between other students and the instructor.

All sensitive material such as your name, email address, etc. will be removed, and also any part of code that is not relevant to the discussion will not be uploaded here.


Article List

Date: 04/21/09 Title: Project teams and themes
Date: 03/22/09 Title: Miniproject details
Date: 02/17/09 Title: Homework 1 Q/A


Articles

Date: 04/21/09 Title: Project teams and themes

Project teams and themes

Presentation schedule:

5/4 Monday 9:10am: 13, 9, 1, 10, 5, 15

5/5 Tuesday 9:10am: 17, 16, 4, 7, 18, 3

5/5 Tuesday 6pm: 6, 8, 11, 14, 12, 2

  1. Lichun Li and Jiaqi Wang: SOM document clustering
  2. Sashkanth Damaraju and Andrew Webb: ANN for multitouch interfaces
  3. Yong Song: Predictive dynamic thermal management
  4. Manju Vijayakumar and Roja Chandanala: Movie recommendation using collaborative filtering and K-NN.
  5. Krishna Kamath: Learning latency among Twitter users
  6. Yuxiang Zhu and Long Nguyen: Handwritten character recognition with ANN
  7. Josh Meyers: EM vs. K-means for restoration of ancient manuscripts
  8. Grant Bremmer: Clustering phylogenetic trees
  9. Ben Stotts: Neuroevolution
  10. Yimin Song and Qianyao Xiong: ANN and HMM to forcast the stock market
  11. Gaurav Yadav: Web-spam identification
  12. Chandan Aggarwal and Vaibhav Jalan: Email spam classification
  13. W. Graham Mueller: Predicting time-series data with Hodrick-Prescott filters.
  14. Ajit Behera: 3D microscopy data analysis
  15. Yuan Zhi: 3D electron microscopy data analysis
  16. Krishna Ganesula: Ant colony optimization for multi agent RL
  17. Phillip Coleman: RL for feature-sensitive motion planning
  18. Pedro Davalos: Image processing with ML
Date: 03/22/09 Title: Miniproject details

Code-base

  1. Backpropagation: backprop-1.6.tar.gz (C++ code -- unix)
  2. Neuroevolution: ga.m (Octave code)
  3. SIDA: sida-nat.tar.gz (Octave code)
Final miniproject details 1. Pick a code-base - YC's backpropagation code (in c++) - YC's neuroevolution code (in octave) - YC's SIDA code for sensorimotor semantics (in octave) - Your own code - Reinforcement learning code (from homework) - Other - A third-party open source 2. Formulate your research problem - Pick task - Locate data set (if needed): see, e.g., UCI ML repository - Design experiments 3. Proposal - Team members: max 2 per team. - What is the research problem? - Why is it important/interesting? - What are other people's approaches? - What are the limitations of those approaches? - What is your approach? - What experiments will you do? - What are the expected results? - Submit by 3/30, in class. 4. Presentation - about 20 minutes. - Present final or preliminary results 5. Final report - 4-5 page, single space report.
Date: 02/17/09 Title: Homework 1 Q/A

Homework 1 Q/A

> Problem 1:
> 
> We can decide the S Boundary and G Boundary by physically observing the
> given diagram.  Is it required to show each step of the candidate
> elimination algorithm or can we mark the boundary on the diagram directly?

        Just show the S and G boundaries. Mark them in the
        diagram and show the intervals.  a <= x <= b , etc.

> Problem 6:
> 
> When you say change of E(w) < 0.00001,   I have two values which can
> denote
> change in E(w). The actual change in E(w) after the previous iteration and
> the gradient value d(E(w))/dw.  Both values are very similar but not
> exactly
> the same, and I am getting a slight change in the total number of
> iterations
> when I use either value.  Am I supposed to use a particular value of the
> two
> or can I choose any of these for the program?

        Use the change in the E(w) value.

> Problem 8:
> It says the answer needs to be a polynomial function of w.  Does this mean
> we should have only polynomial terms (eg: a(n)w^n+a(n-1)w^(n-1)+...)
> etc?
> Or does it mean that we need to have only w as a variable in the
> result(although exponential terms and fractions are allowed in the result
> eg: 1/1+e^(-w4+..) etc..

        You may have the sigmoid function in the result.

> Also do I also need to submit my code for the programs for problems 7,8
> alongwith the solutions?  Are we used a particular programming language?
> I
> have used C.

        If it is not too long (3-4 pages), include the printout of the
        code. You may use any language.


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