CS886 Fall07 - Course Project
- Option A (Literature survey):
- Pick a problem (in ML, NLP or IR) that interests you
- Search the literature for statistical approaches to tackle this
problem
- Survey and discuss the relative strengths of each approach
- Option B (Empirical
evaluation):
- Pick a problem (in ML, NLP or IR) that interests you.
- Implement and experiment with several statistical techniques to
tackle
this problem.
- Option C (Algorithm design):
- Identify a problem (in ML, NLP or IR) for which there are no
satisfying approaches.
- Develop a new statistical technique to tackle this problem.
- Analyze theoretically and/or empirically the performance of
your technique.
- Option D (Theoretical analysis):
- Identify a problem (in ML, NLP or IR) or statistical technique
for which the properties
(e.g., complexity, performance) are not well understood.
- Analyze the properties of this problem or technique.
Proposal (no mark)
- Submit by October 11
- At most one page
- Which option did you pick?
- Option A (Literature survey):
- What is the problem?
- Cite 10 to 15 papers that you plan to survey.
- Option B (Empirical
evaluation):
- What is the problem?
- What statistical techniques do you plan to experiment with?
- Cite 4 to 8 related papers that you plan to survey.
- Option C (Algorithm design):
- What is the problem?
- Why are there no satisfying approaches?
- What is the intuition behind the new technique that you plan to
develop?
- Cite 4 to 8 related papers that you plan to survey.
- Option D (Theoretical analysis):
- What is the problem or technique that you plan to analyze?
- What properties would you like to analyze/prove about this
problem or technique?
- Cite 4 to 8 related papers that you plan to survey.
Presentation (15% of final grade)
- 15 minutes presentation + 5 minutes for questions
- Concentrate on the big picture (do not dwell on the details)
Report (45% of final grade)
- At most 8 pages
- Hand in at the last lecture (Nov 29)
Suggested Structure for the Report
- Option A (Literature survey):
- Introduction
- What is the problem?
- Why is it an important problem?
- Survey
- Summarize the range of techniques by highlighting their
strengths and weaknesses (i.e.,
the 10-15
papers that you read)
- Tip: this summary should not
be a laundry list of techniques with an independent paragraph for each
technique
- Suggestion: organize your summary based on desirable
properties of the techniques
- Analysis:
- What is the state of the art?
- Any open problem?
- Conlusion
- What future research do you recommend?
- Option B (Empirical
evaluation):
- Introduction
- What is the problem?
- Why is it an important problem?
- Techniques to tackle the problem
- Brief survey of previous work concerning this problem (i.e.,
the 4-8
papers that you read)
- Brief description of the techniques chosen and why
- Empirical evaluation
- Compare empirically the techniques for complexity,
performance, ease of use, etc.
- Conclusion:
- What is the best technique?
- Is any technique good enough to declarte the problem solved?
- What future research do you recommend?
- Option C (Algorithm design):
- Introduction
- What is the problem?
- Why can't any of the existing techniques effectively tackle
this problem?
- What is the intuition behind the technique that you have
developed?
- Techniques to tackle the problem
- Brief survey of previous work concerning this problem (i.e.,
the 4-8
papers that you read)
- Describe the technique that you developed
- Brief description of the existing techniques that you will
compare to
- Evaluation
- Analyze and compare (empirically or theoretically) your new
approach to existing approaches
- Conclusion:
- Can your new technique effectively tackle the problem?
- What future research do you recommend?
- Option D (Theoretical analysis):
- Introduction
- What is the problem or technique?
- What properties did you analyze/prove about this problem or
technique?
- Analysis
- Brief survey of previous work concerning this problem (i.e.,
the 4-8
papers that you read)
- Describe the analysis performed
- Conclusion:
- What have you discovered about the technique analyzed?
- What future research do you recommend?