Time Series and Machine Learning Reading Group
February-June 2024, University of Southampton
In this semester we will read a series of papers on deep nerual network (DNN) theories and applications, nonparametric statistics, and casual inference (CI).
This reading group is hybrid –- we meet weekly on Friday 10:30-12:00 (UK time), both at B54/7031 and via MS Teams. Feel free to choose your preferred method to join in.
Please check this website regularly for the most up-to-date arrangement.
Materials
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Week 1. Approximation with CNNs in Sobolev Space: with Applications to Classification (part 1)
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Week 2. Approximation with CNNs in Sobolev Space: with Applications to Classification (part 2)
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Week 3. A Deep Generative Approach to Conditional Sampling (part 1)
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Week 4. Double/debiased machine learning for treatment and structural parameters (part 1)
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Week 5. Double/debiased machine learning for treatment and structural parameters (part 2)
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Week 6. Deep network approximation for smooth functions (part 1)
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Week 7. Deep network approximation for smooth functions (part 2)
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Week 8. A Deep Generative Approach to Conditional Sampling (part 2)
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Week 9. Automatic Change-Point Detection in Time Series via Deep Learning
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Week 10. Modeling of time series using random forests: Theoretical developments (part 1)
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Week 11. Deep Extended Hazard Models for Survival Analysis (part 1)
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Week 12. Modeling of time series using random forests: Theoretical developments (part 2)
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Week 13. Deep Extended Hazard Models for Survival Analysis (part 2)
Group Members
Please contact Chao if want to join in the group
Supplementary References
- Introduction to Nonparametric Estimation.
Alexandre Tsybakov, Springer, 2009.
- Neural Network Learning—Theoretical Fundations
Martin Anthony and Peter L. Bartlett, Cambridge University Press, 1999
- A First Course in Casual Inferences.
Peng Ding, 2023.
- A Distribution-Free Theory of Nonparametric Regression.
László Györfi, Michael Kohler, Adam Krzyżak, and Harro Walk, Springer, 2002.
Roles of Presenter and Discussant
If it is your first time attend a reading group, you might find the reading group tips by Lester Mackey and Percy Liang helpful.
Every time we will have one people (presenter) present the main contents and another people (discussant) raise questions and lead the discussion.
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As a presenter: you should have an in-depth reading and develop a solid understanding of all the details in the assigned topic. You should prepare well, and make sure you deliver a logically clear and technically accessible presentation. In short words, it is your job to have everyone in the meeting understand the main ideas of the reading.
-
As a discussant: you should be more familiar with the content than if you were simply in the group. You don’t need to know everything. You can pause the presentation, ask questions (to the presenter or to the audience), and facilitate discussions. It is your job to help the presenter to have everyone (yourself included!) in the meeting understand the main ideas of the reading and having learned something.
Before each session, although not compulsory I would recommend following amount of time spent on reading:
- Presenter: > 10 hours;
- Discussant: 5 hours;
- General audience: 2 hours.
If you encounter any problem during your reading, feel free to discuss with me or other staff members.
Past Reading Groups:
Webpage maintained by Chao Zheng. Last updated on 18/11/2022
Time Series and Machine Learning Reading Group
February-June 2024, University of Southampton
In this semester we will read a series of papers on deep nerual network (DNN) theories and applications, nonparametric statistics, and casual inference (CI).
This reading group is hybrid –- we meet weekly on Friday 10:30-12:00 (UK time), both at B54/7031 and via MS Teams. Feel free to choose your preferred method to join in.
Timetable (provisional)
Please check this website regularly for the most up-to-date arrangement.
Materials
Week 1. Approximation with CNNs in Sobolev Space: with Applications to Classification (part 1)
Week 2. Approximation with CNNs in Sobolev Space: with Applications to Classification (part 2)
Week 3. A Deep Generative Approach to Conditional Sampling (part 1)
Week 4. Double/debiased machine learning for treatment and structural parameters (part 1)
Week 5. Double/debiased machine learning for treatment and structural parameters (part 2)
Week 6. Deep network approximation for smooth functions (part 1)
Week 7. Deep network approximation for smooth functions (part 2)
Week 8. A Deep Generative Approach to Conditional Sampling (part 2)
Week 9. Automatic Change-Point Detection in Time Series via Deep Learning
Week 10. Modeling of time series using random forests: Theoretical developments (part 1)
Week 11. Deep Extended Hazard Models for Survival Analysis (part 1)
Week 12. Modeling of time series using random forests: Theoretical developments (part 2)
Week 13. Deep Extended Hazard Models for Survival Analysis (part 2)
Group Members
Please contact Chao if want to join in the group
Supplementary References
Alexandre Tsybakov, Springer, 2009.
Martin Anthony and Peter L. Bartlett, Cambridge University Press, 1999
Peng Ding, 2023.
László Györfi, Michael Kohler, Adam Krzyżak, and Harro Walk, Springer, 2002.
Roles of Presenter and Discussant
If it is your first time attend a reading group, you might find the reading group tips by Lester Mackey and Percy Liang helpful.
Every time we will have one people (presenter) present the main contents and another people (discussant) raise questions and lead the discussion.
As a presenter: you should have an in-depth reading and develop a solid understanding of all the details in the assigned topic. You should prepare well, and make sure you deliver a logically clear and technically accessible presentation. In short words, it is your job to have everyone in the meeting understand the main ideas of the reading.
As a discussant: you should be more familiar with the content than if you were simply in the group. You don’t need to know everything. You can pause the presentation, ask questions (to the presenter or to the audience), and facilitate discussions. It is your job to help the presenter to have everyone (yourself included!) in the meeting understand the main ideas of the reading and having learned something.
Before each session, although not compulsory I would recommend following amount of time spent on reading:
Past Reading Groups:
Webpage maintained by Chao Zheng. Last updated on 18/11/2022