Week 7: Research Write-up

Announcements

  • Lab 6 is due 03/01 by 23:59 EST.

  • Midterm is due 03/02 by 23:59 EST.

  • Lab 7 will be available Wednesday, 03/02. It is a team assignment.

  • Lectures and labs this week are In Person, office hours are via ZOOM.

  • Lectures video recordings are in our shared Google folder.

  • Class participation, EdSTEM, Figma, and the Group 1 of The six groups for lecture notes.

Week 7 Topics

  • Research Analysis Cont.

  • Example Papers

  • Your Research Analysis

  • The 'Method' Section

  • The 'Result' Section

  • The 'Discussion' Section

Monday

Senior Comprehensive

  • project-based course

  • CPSC 063: Artificial Intelligence

  • CPSC 081: Adaptive Robotics

  • CPSC 091.3: Machine Learning and Brain-Computer Interfaces

In-class exercises:

  • Are you thinking of a Senior Comprehensive? Is this one a good starting point?

  • Post it on Figma

Esemble Methods Cont.

In-class exercises:

  • Are you using Ensemble Methods? if so, which one? and how?

  • Post it on Figma

Parameter Engineering

In-class exercises:

  • What Hyperparameter have you used in your algorithms?

  • Post it on Figma

The 'Discussion' Section

  • Limitations

  • Future Work

  • Conclusion

  • Revisit 'Title', 'Keywords', and 'Abstract'

  • learn from papers we have reviewed

Wednesday

Lab 7

  • Reviewer Guide

  • Double-Blind

  • Best Practices

  • Feedback Timeline, labs and Midterm

In-class exercises:

  • Reviewer Guide

  • Double-Blind

  • 'Your comments should be detailed, specific, and polite. Please avoid vague, subjective complaints. '

  • 'Always be constructive and help the authors understand your viewpoint, without being dismissive or using inappropriate language. '

Summary of the first half

  • Others' Research

  • Your research

Midterm Evaluation

  • Course

  • Instructor

  • Student

In-class exercises:

  • What went well?

  • What can be improved?

  • Post it on Figma

Friday

Midterm Course Evaluation

  • 4.2. Individual Submission

  • Email me earlier to make the changes to the courses.

  • Recommended submitting by next Tuesday, 03/08/2022, 23:59 EST.

Final Project

  • Time Management (toolset)

  • Spring break

  • Thirty-Five hours left

In-class exercises:

  • Your plan for the next two months

Summary of Algorithms

  • Three minimum requirements

    1. (Linear Discriminant Analysis) LDA

    2. (Support Vector Machine) SVM

    3. (Random Forest) RF

  • Two extra

    1. Nearest Neighbors (kNN)

    2. Ensemble Methods (boosting, bagging, stacking, and voting)

In-class exercises:

  • Which algorithms have you learned?

  • Which algorithms have you applied to your dataset?

  • Which algorithm outperforms others in your paper?

Summary of Papers

In-class exercises:

  • Which poster is a good example for your two-page poster?

  • Which paper is a good example for your ten-page poster?

Summary of Reviews

In-class exercises:

  • Which reviewer feedback example do you feel is the most helpful?

  • What’s your takeaway message for the double-blind peer review process?

Summary of Labs

  • Takeaway message

  • Action items

In-class exercises:

  • Which lab do you feel is the most difficult?

  • Which lab took you the longest time?