DBML 2022: International workshop on databases and machine learning Virtual event Kuala Lumpur, Malaysia, May 9, 2022 |
Conference website | https://www.wis.ewi.tudelft.nl/dbml2022 |
Submission link | https://easychair.org/conferences/?conf=dbml22 |
Submission deadline | January 27, 2022 |
About the workshop
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After the increased adoption of machine learning (ML) in various applications and disciplines, a synergy between thedatabase (DB) systems and ML communities emerged. Steps involved in an ML pipeline, such as data preparation and cleaning,feature engineering and management of the ML lifecycle, can benefit from research conducted by the data management community.For example, the management of the ML lifecycle requires mechanisms for modeling, storing and querying ML artifacts.Moreover, in many use cases pipelines require a mixture of relational and linear algebra operators raising the questionof whether a seamless integration between the two algebras is possible.In the opposite direction, ML techniques are explored in core components of database systems, e.g., query optimization,indexing and monitoring. Traditionally hard problems in databases, such as cardinality estimation, or problems with highhuman supervision like DB administration, might benefit more from learning algorithms than from rule-based orcost-based approaches.
The workshop aims at bringing together researchers and practitioners in the intersection of DB and ML research,providing a forum for DB-inspired or ML-inspired approaches addressing challenges encounteredin each of the two areas. In particular, we welcome new research topics combining the strengths of both fields.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference.
The workshop will accept both regular papers (8 pages) and short papers (4 pages - work in progress, vision/outrageous ideas).
Submission Website: https://easychair.org/conferences/?conf=dbml22
Important Dates
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Paper submission deadline: Jan 14, 2022
Authors notification: Feb 22, 2022
Camera ready version: Mar 08, 2022
Workshop day: May 9, 2022
List of Topics
Topics of particular interest in the workshop include, but are not limited to:
- Data collection and preparation for ML applications
- Declarative machine learning on databases, data warehouses or data lakes
- Hybrid optimization techniques for databases and machine learning
- Model-aware data discovery, cleaning, and transformation
- Benchmarking ML-oriented data management systems (data augmentation, data cleaning, etc)
- Data management during the life cycle of ML models
- Novel data management systems for accelerating training and inference of ML models
- DB-inspired techniques for modeling, storage and provenance of ML artifacts
- Learned database design, configuration and tuning
- Machine learning for query optimization
- Applied machine learning/deep learning for data integration
- ML-enabled data exploration and discovery in data lakes
- ML functionality inside DBMS
Committees
Organizing committee
- Rihan Hai (TU Delft)
- Nantia Makrynioti (CWI)
- Ioana Manolescu (INRIA)
Venue
The workshop will be a virtual event.
Contact
All questions about submissions should be emailed to Dr. Hai (R.Hai@tudelft.nl) or Dr. Makrynioti (Nantia.Makrynioti@cwi.nl)