Week 2
From Research management course
The goal of this week is comprehend the main goal of your project and write about it.
Contents
Select your project (Spring 2022)
To select your project:
- Look through the list of projects.
- Find information about the experts and consultants.
- Select your projects in [1].
- Wait for confirmation from ...
- Put confirmed topics to the Group table
- Write your consultant (politely).
A: Abstract
Write a draft of your abstract. Think of a motivation. The abstract shall not exceed 600 characters. It may contain:
- wide-range field of the investigated problem,
- narrow problem to focus on,
- features and conditions of the problem,
- the novelty (please not exaggerate),
- application to illustrate with (put the results here later).
Land your project
- Обсудить с консультантом проект, понять цели, задачи, проблемы.
- Найти в организации https://github.com/Intelligent-Systems-Phystech репозиторий своего проекта или создать его с названием формата Project-N или через акроним проекта, примеры.
- Записать ссылку на репозиторий to the Group table.
- Create the folder structure:
- docs,
- code,
- data,
- [figs].
- Put the direct link to the paper in the Group table, so that everyone could access it.
- Rename article.tex to Surname2020Title.tex
- Check the both .tex and .pdf files are downloaded.
- Fill the readme.md file in the github project.
- (Если проект продолжающийся) Создать личную папку в репозитории проекта, название в формате Surname2018Title.
- Поместить файл (из ДЗ 1) с шаблоном статьи в личную папку, название в формате Surname2018Title.tex.
- Записать ссылку на файл PDF с текстом статьи to the Group table on Machinelearning.ru в таблицу.
- Совет: копируйте ссылку как адрес кнопки Download файла PDF, который находится в репозитории.
- Создать документ-черновик обзора литературы формата LinkReview, поставить на него ссылку to the Group table on Machinelearning.ru в таблицу.
- Рекомендуется кроме литературы заносить в LinkReview ссылки на источники данных, на код и библиотеки.
- Совет: создать групповой чат.
L: Literature
We use the LinkReview draft format to share our evanescent ephemeral ideas and impressions we have during the literature reading.
- Collect the list of references including:
- state-of-the-art reviews, tutorials,
- fundamental solutions to the problem,
- the basic algorithm to solve your problem,
- alternative algorithms,
- [changes in the research directions],
- data sets and experiments,
- the papers that use these data sets
- applications of the results,
- names of researchers, who solve this problem,
- their students and teams,
- those, who refer to their works.
- Balance the list of the new and well-known works.
- Keep up-to date the list of keywords to search with.
- Continuously fill your LinkReview.
- Plan Introduction (see the next todo list), namely collect:
- keywords as the basic termini; those who brigs good search results are useful,
- what the paper devoted to,
- the investigated problem,
- the central idea,
- literature review,
- the authors' contribution.
B: Beginner's-talk
Short 45-second introductory talk. Plan of the talk:
- The project goal. What is the motivation, the goal to reach?
- The main idea. What is the message?
- The expected result. What is your delivery, your impact, novelty?
There is no time to show a slide or draw a plot on the blackboard. It is recommended to rehearse the report. Week 3 starts with your talk.
Resources
- Slides for week 2.
- [Video for week 2].
- Bibliographic databases
- The Collection of Computer Science Bibliographies
- List of academic databases and search engines in Wikipedia
- Refer to BibTeX in Wikipedia
- An introduction updated after a peer-review.
- Examples of rewiev-and-planning drafts LinkReview раз, два.
- Демотиватор про Карлсона
- How to Read a Paper, 2016, S. Keshav
Советы по пользованию репозиторием
- GitHub: клонируйте мастер и заливайте правки в него, если работаете только со своим кодом. См. краткое руководство по работе с GitHub.
- Update first, Commit after (Pull first, Push after)
- Your own work only, no external publications
- No big files (put link to external datasets)
- No temporary nor dummy files
Прочитать, чем отличается branch от fork