Fall 2024
Data Science Seminar: Model Selection
Lecturers: Mourad Khayati and Alberto Lerner
Teaching language: English
Level: MSc students
Academic year: Fall 2024
Overview
The data science seminar involves presentations covering recent topics in data science. The area of this year’s seminar is model. In the scope of this seminar, we investigate papers that describe model selection algorithms and systems. The papers explore techniques to configure, compare, and select the best-performing model among a set of seed models. Those techniques are applied to solve
various tasks and involve datasets of different formats.
Structure
The goal for the students is to learn how to critically read and study research papers, describe a paper in a report, and present it in a seminar. Under supervision, students will select one paper to study and compare it with related work. This seminar aims to help students gather in-depth knowledge of an advanced topic and develop the skills required to describe a complex problem from the time series field in the form of both a presentation, a written report, and an empirical evaluation.
IMPORTANT NOTE: The papers will be distributed on a first-come, first-serve basis.
Evaluation and Expectations
The final grade depends on the quality of the report, presentation, reproducibility experiments, and active participation during the seminar. Each participant prepares a self-contained report of min 6 pages and gives a presentation of 30 minutes. The report should describe the proposed benchmark in detail. The report might contain a small running example, counterexample(s), and should explore the extreme cases where the evaluated systems and algorithms would perform best and worst. The reproducibility consists of reproducing the same set of experiments introduced in the paper using a different setup (dataset, metric, parameters, etc.).
Advice on how to:
IMPORTANT NOTE: Attendance is mandatory for the two-class seminar sessions. The total number of participants will be limited to 10.
Schedule
Kickoff Meeting. Date: Tue, 24.09.2024, 14:15-15:30, room: TBD
Setup and organization of the seminar and paper assignment
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Date: Tue, 05.11.2024
Report deadline Batch1
Date: Tue, 12.11.2024, all day, room: C433 or C411
Office meeting with students from Batch1
First Seminar Session. Date: Tue, 19.11.2024, 14:15-18:00, room: TBD
Presentations of Batch1
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Date: Tue, 26.11.2024
Report deadline of Batch2
Date: Tue, 03.12.2024, all day, room: C433 or C411
Office meeting with students from Batch2
Second Seminar Session. Date: Tue, 10.12.2024, 14:15-18:00, room: TBD
Presentations of Batch2
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Date: Tue, 14.01.2025
Deadline final Report of Batch1 and Batch2
Paper Assignment
The papers will be distributed on a first-come, first-serve basis. To select one paper from the list of papers, please use the following link.
Paper & code | Presentation Date | Presenter | Mentor |
TSC-AutoML: Meta-learning for Automatic Time Series Classification Algorithm Selection, ICDE’2023 | - | - | Mourad Khayati |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series, VLDB’24 | - | - | Mourad Khayati |
Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems, VLDB’24 | - | - | Mourad Khayati |
Raha: A Configuration-Free Error Detection System, SIGMOD’19 | - | - | Mourad Khayati |
SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting, VLDB’23 | - | - | Mourad Khayati |
TBA | - | - | Alberto Lerner |
TBA | - | - | Alberto Lerner |
TBA | - | - | Alberto Lerner |
TBA | - | - | Alberto Lerner |
TBA | - | - | Alberto Lerner |