Интеллектуальный анализ данных (О.Ю. Бахтеев, В.В. Стрижов)/Осень 2022

Материал из MachineLearning.

(Различия между версиями)
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(Intelligent data analysis)
(Topics to discuss)
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==Topics to discuss==
==Topics to discuss==
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* Differential alignment of continuous-time (series) videos
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* Taken's theorem and convergent cross-mapping
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* Graph diffusion models with PDE examples
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* Dimensionality reduction on Riemannian manifolds (for videos)
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==Examples and references==
==Examples and references==
* [https://towardsdatascience.com/questions-96667b06af5#dee8 TDS guidelines]
* [https://towardsdatascience.com/questions-96667b06af5#dee8 TDS guidelines]

Версия 08:57, 8 сентября 2022

Each Saturday 13:10 at the channel m1p.org/go_zoom


Intelligent data analysis

This course develops skills of communication. The goal is to deliver your message to wide auditory of professionals. The form of delivery is a short paper. It results several discussions in our team according to the plan below.

Schedule and grading

Workflow

  1. Select topic (report)
  2. Prepare material (present 5-10 min and discuss)
  3. Make presentation (20 min and questions)
  4. Write your text (2 pages and discuss)
  5. Publish your text (link)

Calendar

  • Sep: 16, 23, 30 select
  • Oct: 7, 14, 21, 28 talk
  • Nov: 4, 11 talk, 18, 25 text
  • Dec: 2 link, 9 fin

Insert your name and direct link to materials. Each column must carry your name.

Date Select Talk Text
16nxt Islamov, Strijov
23sep ...
30 ...
7oct x ...
14 ...
21 ...
28 ...
4nov ...
11 ...
18 x ...
25 x ...

Course page, and projects

  • TODO Course page
  • TODO Projects

The result links before 2nd of december

Topics to discuss

  • Differential alignment of continuous-time (series) videos
  • Taken's theorem and convergent cross-mapping
  • Graph diffusion models with PDE examples
  • Dimensionality reduction on Riemannian manifolds (for videos)

Examples and references

Личные инструменты