CMSC 691B Discussion Questions
Learning and Order
Cohen et al., "Learning to order things"
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What are the main claims of the paper? Does the paper present theoretical
and/or empirical evidence for these claims?
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Does the paper position itself thoroughly and accurately with respect to
related work?
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Specific technical questions:
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What are the two stages in their "two-stage approach"?
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What are the advantages and disadvantages in separating the problem into
these two stages? Is one of the stages more thoroughly worked out/addressed
in this paper?
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What is an online learning algorithm? Why do they use one for this
problem?
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What are the ranking experts that are used in the first phase? How
would you develop a set of ranking experts for a new problem? What ranking
experts do they use for their results?
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How does the Hedge algorithm work? What is a loss function, and
how is the loss function used by this algorithm defined? Do yout hink this
is a good loss function to use?
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What are the differences between the alternative approximately-optimal-ordering
algorithms?
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What's being evaluated by the experiments presented in Section 5? Are these
results convincing? Why or why not?
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What are the key results of the paper?
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What do you think are the most important/interesting next steps/future
work for this paper?
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What references would you follow up on if you were to do further
reading on this topic?
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What were the good and bad aspects of the presentation (organization, writing
quality, clarity) of this paper? Is the paper self-contained, or would
you need to do further background reading (or correspond with the authors )
to understand the details of the methods and results?
Kamishima and Akaho, "Learning from order examples"
What are the main claims of the paper? Does the paper present theoretical
and/or empirical evidence for these claims?
Does the paper position itself thoroughly and accurately with respect to
related work?
Specific technical questions:
What does this paper use as the loss function for measuring the effectiveness
of the algorithm? Do you think this is a good loss function to use? How
does it differ from the loss function used by Cohen et al.?
What is the difference between a "classification-based" and a "regression-based" approach
for learning ordering functions?
What is the "Bayesian estimator with Dirichlet prior" (p. 646) used for?
What is the difference between the SumClass and ProductClass sorting strategies?
How woudl one decide which to use?
What is the "Type I quantification method" used for the regression approach?
What is being evaluated by the experiments in Section 5? Are these results
convincing? Why or why not? Are the conclusions drawn by the authors supported
by the results?
What are the key results of the paper?
What do you think are the most important/interesting next steps/future
work for this paper?
What references would you follow up on if you were to do further
reading on this topic?
What were the good and bad aspects of the presentation (organization, writing
quality, clarity) of this paper? Is the paper self-contained, or would
you need to do further background reading (or correspond with the authors )
to understand the details of the methods and results?
Comparing the papers
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One of these papers is a conference paper; the other is a journal paper.
How are the differences between these types of publications apparent?
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The Kamishima and Akaho paper cites the Cohen et al. paper. Could this
be seen as an extension of that work? Is their analysis of the earlier
paper, and their positioning of their work relative to the earlier work,
correct/useful?
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Cohen et al. give several reasons not to use item-set orderings
as input to the learning process. What are these reasons? Conversely, Kamishima
and Akaho indicate that their use of item-set orderings as input is one
of the key differences/advantages of their approach. Is the latter claim
supported by the paper? Do you find one of these approaches more convincing?
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Does the later paper represent a significant improvement or extension over
earlier work?