Difference between revisions of "Step 7"

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== The seminar ==
 
== The seminar ==
# [The warm-up 5-minute test]  
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# [https://forms.gle/mNNYqWjc2tdq3vQB6 The warm-up 5-minute test]  
# The model selection problem statement
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# The expert estimations and integral indicators
# The Bayesian inference
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# Introduction; strengths and weaknesses of basic solutions
# How to read papers and gather references
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# Form your LinkReview and .[https://en.wikipedia.org/wiki/BibTeX#Database_files bib] with [https://www.jabref.org/ JabRef] using [https://en.wikipedia.org/wiki/Digital_object_identifier DOI]
# Buidling the comparative table
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# Discuss how to fill the LinkReview [[Week_2#L:_Literature|with L:Literature]]
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# Make a table of them on your homework
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# Dicsuss the project comparison
  
 
==Resources==
 
==Resources==
Step 7 YouTube []
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Step 7 YouTube [https://www.youtube.com/watch?v=i_YVhwS3vf8 video]
  
 
==Homework==
 
==Homework==
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# Put the short version of your analysis in the table.  
 
# Put the short version of your analysis in the table.  
 
# Fill in the table [https://github.com/vadim-vic/the-Art-homework/blob/main/Name-Step-7.tex in your repository].
 
# Fill in the table [https://github.com/vadim-vic/the-Art-homework/blob/main/Name-Step-7.tex in your repository].
# Put the link to your analysis [https://forms.gle/C981rjxwerpL7QoR6 here, Step-7].
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# Put the link to your analysis [https://forms.gle/C4mn6AXEX5fKry2i6 here, Step-7].
  
 
While completing the table, remember the formula for an engineering project description: "We propose a solution that offers a unique feature, distinguishing it from other solutions." Of course, each part needs an explanation.
 
While completing the table, remember the formula for an engineering project description: "We propose a solution that offers a unique feature, distinguishing it from other solutions." Of course, each part needs an explanation.

Latest revision as of 13:32, 16 November 2024

"If I have seen further, it is because I have stood on the shoulders of giants", – Isaac Newton wrote this in a letter in 1675.

We establish a solid foundation for our research to deliver results of better quality and higher impact with less effort. This foundation comprises essentials, overviews, state-of-the-art, and alternatives to our solution. Not to mention the supplementary materials like references to the algorithms and data in your computational experiment.


The seminar

  1. The warm-up 5-minute test
  2. The expert estimations and integral indicators
  3. Introduction; strengths and weaknesses of basic solutions
  4. Form your LinkReview and .bib with JabRef using DOI
  5. Discuss how to fill the LinkReview with L:Literature
  6. Make a table of them on your homework
  7. Dicsuss the project comparison

Resources

Step 7 YouTube video

Homework

Each solution to your problem has its pros and cons. List them all.

  1. Collect references for your project according to the plan.
  2. While collecting put your notes to the temporary file LinkReview (see examples below) or to the .bib and .tex
  3. Put them into the .bib using JabRef or another tool that generates the bibliographic record using doi.
  4. Analyse each solution's pros and cons according to the project's quality criteria.
  5. Put the short version of your analysis in the table.
  6. Fill in the table in your repository.
  7. Put the link to your analysis here, Step-7.

While completing the table, remember the formula for an engineering project description: "We propose a solution that offers a unique feature, distinguishing it from other solutions." Of course, each part needs an explanation.

Note: The whole section Introduction is not required.

Examples

  1. Look through the table of reports and see some particular LinkReview files.
  2. Examples of the comparative tables
    1. Generation of simple structured IR functions by genetic algorithm without stagnation
    2. Feature Selection for ECoG-based Brain-Computer Interface
  3. See parts of Introduction (to put it in the LinkReview as a draft)
    1. Related works: Stresstest procedures for feature selection algorithms
    2. The main contributions of this paper are: Comprehensive study of feature selection methods to solve multicollinearity problem according to evaluation criteria
  4. For the future materials see a problem statement (beware the spherical horse in a vacuum)