Time Series and Machine Learning Reading Group
February-June 2023, University of Southampton
In this semester we will read a series of papers on deep nerual network (DNN) theories for nonparametric/quantile regression, and state-of-art time series forecasting using DNN. .
This reading group is hybrid — we meet weekly on Friday 13:30-15:00 (UK time), both at B54/5001 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. Deep Neural Networks for Estimation and Inference (part 1)
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Week 2. Deep Neural Networks for Estimation and Inference (part 2)
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Week 3. Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
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Week 4. Error Bounds for Approximations with Deep ReLU Networks (part 1)
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Week 5. Error Bounds for Approximations with Deep ReLU Networks (part 2)
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Week 6. Optimal Approximation of Continuous Functions by Very Deep ReLU Networks
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Week 7. Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition (part 1)
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Week 8.N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting
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Week 9. Combining Counterfactual Outcomes and ARIMA Models for Policy Evaluation
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Week 10. Causal Inference Using Potential Outcomes
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Week 11. Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations
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Week 12. A Penalized Synthetic Control Estimator for Disaggregated Data
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Week 13. On The Rate of Convergence of A Neural Network Regression Estimate Learned by Gradient Descent
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Week 14. Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition (part 2)
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Week 15. Asymptotic Properties of Neural Network Sieve Estimators
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Week 16. The Augmented Synthetic Control Method
Group Members
Please contact Chao if want to join in the group
Supplementary References
- Quantile Regression.
Roger Koenker, Cambridge Uni Press, 2005.
- Introduction to Nonparametric Estimation.
Alexandre Tsybakov, Springer, 2009.
- 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 2023, University of Southampton
In this semester we will read a series of papers on deep nerual network (DNN) theories for nonparametric/quantile regression, and state-of-art time series forecasting using DNN. .
This reading group is hybrid — we meet weekly on Friday 13:30-15:00 (UK time), both at B54/5001 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. Deep Neural Networks for Estimation and Inference (part 1)
Week 2. Deep Neural Networks for Estimation and Inference (part 2)
Week 3. Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
Week 4. Error Bounds for Approximations with Deep ReLU Networks (part 1)
Week 5. Error Bounds for Approximations with Deep ReLU Networks (part 2)
Week 6. Optimal Approximation of Continuous Functions by Very Deep ReLU Networks
Week 7. Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition (part 1)
Week 8.N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting
Week 9. Combining Counterfactual Outcomes and ARIMA Models for Policy Evaluation
Week 10. Causal Inference Using Potential Outcomes
Week 11. Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations
Week 12. A Penalized Synthetic Control Estimator for Disaggregated Data
Week 13. On The Rate of Convergence of A Neural Network Regression Estimate Learned by Gradient Descent
Week 14. Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition (part 2)
Week 15. Asymptotic Properties of Neural Network Sieve Estimators
Week 16. The Augmented Synthetic Control Method
Group Members
Please contact Chao if want to join in the group
Supplementary References
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