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ORCIDBenjamin Hilprecht
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2020 – today
- 2023
[c6]Benjamin Hilprecht
, Christian Hammacher, Eduardo Souza dos Reis, Mohamed Abdelaal, Carsten Binnig:
DiffML: End-to-end Differentiable ML Pipelines. DEEM@SIGMOD 2023: 7:1-7:7- [i11]Liane Vogel, Benjamin Hilprecht, Carsten Binnig:
Towards Foundation Models for Relational Databases [Vision Paper]. CoRR abs/2305.15321 (2023) - [i10]Benjamin Hilprecht, Kristian Kersting, Carsten Binnig:
SPARE: A Single-Pass Neural Model for Relational Databases. CoRR abs/2310.13581 (2023) - 2022
- [b1]Benjamin Hilprecht:
Data-Efficient Learned Database Components. Technical University of Darmstadt, Germany, 2022 - [j4]Benjamin Hilprecht, Carsten Binnig:
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction. Proc. VLDB Endow. 15(11): 2361-2374 (2022) - [j3]Marius Gassen, Benjamin Hättasch, Benjamin Hilprecht, Nadja Geisler, Alexander Fraser, Carsten Binnig:
Demonstrating CAT: Synthesizing Data-Aware Conversational Agents for Transactional Databases. Proc. VLDB Endow. 15(12): 3586-3589 (2022) - [c5]Benjamin Hilprecht, Carsten Binnig:
One Model to Rule them All: Towards Zero-Shot Learning for Databases. CIDR 2022 - [i9]Benjamin Hilprecht, Carsten Binnig:
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction. CoRR abs/2201.00561 (2022) - [i8]Marius Gassen, Benjamin Hättasch, Benjamin Hilprecht, Nadja Geisler, Alexander Fraser, Carsten Binnig:
Demonstrating CAT: Synthesizing Data-Aware Conversational Agents for Transactional Databases. CoRR abs/2203.14144 (2022) - [i7]Benjamin Hilprecht, Christian Hammacher, Eduardo Souza dos Reis, Mohamed Abdelaal, Carsten Binnig:
DiffML: End-to-end Differentiable ML Pipelines. CoRR abs/2207.01269 (2022) - 2021
- [c4]Benjamin Hilprecht, Carsten Binnig:
ReStore - Neural Data Completion for Relational Databases. SIGMOD Conference 2021: 710-722 - [i6]Benjamin Hilprecht, Carsten Binnig:
One Model to Rule them All: Towards Zero-Shot Learning for Databases. CoRR abs/2105.00642 (2021) - [i5]Benjamin Hilprecht, Carsten Binnig:
ReStore - Neural Data Completion for Relational Databases. CoRR abs/2105.12457 (2021) - 2020
- [j2]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig:
DeepDB: Learn from Data, not from Queries! Proc. VLDB Endow. 13(7): 992-1005 (2020) - [c3]Benjamin Hilprecht, Carsten Binnig, Tiemo Bang, Muhammad El-Hindi, Benjamin Hättasch, Aditya Khanna, Robin Rehrmann, Uwe Röhm, Andreas Schmidt, Lasse Thostrup, Tobias Ziegler:
DBMS Fitting: Why should we learn what we already know? CIDR 2020 - [c2]Benjamin Hilprecht, Carsten Binnig, Uwe Röhm:
Learning a Partitioning Advisor for Cloud Databases. SIGMOD Conference 2020: 143-157
2010 – 2019
- 2019
- [j1]Benjamin Hilprecht, Martin Härterich, Daniel Bernau:
Monte Carlo and Reconstruction Membership Inference Attacks against Generative Models. Proc. Priv. Enhancing Technol. 2019(4): 232-249 (2019) - [c1]Benjamin Hilprecht, Carsten Binnig, Uwe Röhm:
Towards learning a partitioning advisor with deep reinforcement learning. aiDM@SIGMOD 2019: 6:1-6:4 - [i4]Benjamin Hilprecht, Carsten Binnig, Uwe Röhm:
Learning a Partitioning Advisor with Deep Reinforcement Learning. CoRR abs/1904.01279 (2019) - [i3]Benjamin Hilprecht, Martin Härterich, Daniel Bernau:
Reconstruction and Membership Inference Attacks against Generative Models. CoRR abs/1906.03006 (2019) - [i2]Benjamin Hilprecht, Andreas Schmidt, Moritz Kulessa, Alejandro Molina, Kristian Kersting, Carsten Binnig:
DeepDB: Learn from Data, not from Queries! CoRR abs/1909.00607 (2019) - 2018
- [i1]Moritz Kulessa, Alejandro Molina, Carsten Binnig, Benjamin Hilprecht, Kristian Kersting:
Model-based Approximate Query Processing. CoRR abs/1811.06224 (2018)
Coauthor Index
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