Recent Developments in DB&IS (Seminar)
In order to attend, students must follow the registration process outlined below. Each chosen student will be assigned a research paper that they must present in a 45-minute talk, followed by a Q&A session. The presentation and Q&A will be conducted exclusively in English. Finally, students are required to submit a brief 4-page report on the paper within two weeks of the presentation.
Registration Process
- To register, download the JSON template, rename it to {yourmatriculationnumber}.json, fill the details, and send it via email under Contact.
- We'll announce the kick-off meeting date once registration is complete. The meeting is mandatory and will cover organizational aspects.
Deadlines
- Registration: 12-04-2024
- No-left-todo slides: tbd
- Report submission: tbd
Log
- 15/04/2024 - Papers assigned.
- 07/03/2024 - Registration dates announced.
Papers
| ID | Paper Title | Student | Link |
|---|---|---|---|
| 1 | Automatic Database Management System Tuning Through Large-scale Machine Learning | Yvonne Bötzel | https://doi.org/10.1145/3035918.3064029 |
| 2 | DB-BERT: A Database Tuning Tool that “Reads the Manual” | Paul Ohler | https://dl.acm.org/doi/10.1145/3514221.3517843 |
| 3 | Cross-Modal Data Discovery over Structured and Unstructured Data Lakes | Erik Schwede | https://dl.acm.org/doi/pdf/10.14778/3611479.3611533 |
| 4 | Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes | Jan Heidemann | https://dl.acm.org/doi/pdf/10.1145/3626755 |
| 5 | Panakos: Chasing the Tails for Multidimensional Data Streams | Omar Al-Kubati | https://www.vldb.org/pvldb/vol16/p1291-zhao.pdf |
| 6 | Sieve: A Learned Data-Skipping Index for Data Analytics | Manas Lalit Mahajan | https://www.vldb.org/pvldb/vol16/p3214-tong.pdf |
| 7 | Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores | Jan Karklins | https://arxiv.org/abs/1203.0055 |
| 8 | BtrBlocks: Efficient Columnar Compression for Data Lakes | Joseph Blessingh Israel | https://dl.acm.org/doi/10.1145/3589263 |
| 9 | Grouping Time Series for Efficient Columnar Storage | Simon Eggers | https://dl.acm.org/doi/10.1145/3588703 |
| 10 | APEX: A High-Performance Learned Index on Persistent Memory | Jonathan Püttmann | https://www.vldb.org/pvldb/vol15/p597-lu.pdf |
| 11 | Sample-Efficient Cardinality Estimation Using Geometric Deep Learning | Daniel Fischer | https://www.vldb.org/pvldb/vol17/p740-reiner.pdf |