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Claudio Hartmann
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Cardinality estimation with local deep learning models
L Woltmann, C Hartmann, M Thiele, D Habich, W Lehner
Proceedings of the second international workshop on exploiting artificial …, 2019
1082019
Simplicity Done Right for Join Ordering
A Hertzschuch, C Hartmann, D Habich, W Lehner
CIDR, 2021
302021
Forecasting the data cube: A model configuration advisor for multi-dimensional data sets
U Fischer, C Schildt, C Hartmann, W Lehner
2013 IEEE 29th International Conference on Data Engineering (ICDE), 853-864, 2013
242013
Exploiting big data in time series forecasting: A cross-sectional approach
C Hartmann, M Hahmann, W Lehner, F Rosenthal
2015 IEEE international conference on data science and advanced analytics …, 2015
222015
PostCENN: PostgreSQL with Machine Learning Models for Cardinality Estimation
L Woltmann, D Olwig, C Hartmann, D Habich, W Lehner
122021
CSAR: the cross-sectional autoregression model for short and long-range forecasting
C Hartmann, F Ressel, M Hahmann, D Habich, W Lehner
International Journal of Data Science and Analytics 8, 165-181, 2019
112019
CSAR: The cross-sectional autoregression model
C Hartmann, M Hahmann, D Habich, W Lehner
2017 IEEE international conference on data science and advanced analytics …, 2017
82017
Turbo-charging SPJ query plans with learned physical join operator selections
A Hertzschuch, C Hartmann, D Habich, W Lehner
Proceedings of the VLDB Endowment 15 (11), 2706-2718, 2022
72022
Machine learning-based cardinality estimation in dbms on pre-aggregated data
L Woltmann, C Hartmann, D Habich, W Lehner
arXiv preprint arXiv:2005.09367, 2020
72020
Web-based benchmarks for forecasting systems: The ecast platform
R Ulbricht, C Hartmann, M Hahmann, H Donker, W Lehner
Proceedings of the 2016 International Conference on Management of Data, 2169 …, 2016
72016
Particulate Matter Matters—The Data Science Challenge@ BTW 2019
HJ Meyer, H Grunert, T Waizenegger, L Woltmann, C Hartmann, ...
Datenbank-Spektrum, 1-18, 2019
62019
Aggregate-based training phase for ML-based cardinality estimation
L Woltmann, C Hartmann, D Habich, W Lehner
Datenbank-Spektrum 22 (1), 45-57, 2022
52022
Best of both worlds: combining traditional and machine learning models for cardinality estimation
L Woltmann, C Hartmann, D Habich, W Lehner
Proceedings of the Third International Workshop on Exploiting Artificial …, 2020
52020
Challenges for context-driven time series forecasting
R Ulbricht, H Donker, C Hartmann, M Hahmann, W Lehner
Journal of Data and Information Quality (JDIQ) 7 (1-2), 1-4, 2016
52016
Fastgres: Making learned query optimizer hinting effective
L Woltmann, J Thiessat, C Hartmann, D Habich, W Lehner
Proceedings of the VLDB Endowment 16 (11), 3310-3322, 2023
42023
Season-and trend-aware symbolic approximation for accurate and efficient time series matching
L Kegel, C Hartmann, M Thiele, W Lehner
Datenbank-Spektrum 21, 225-236, 2021
42021
Sensor-based jump detection and classification with machine learning in trampoline gymnastics
L Woltmann, C Hartmann, W Lehner, P Rausch, K Ferger
German Journal of Exercise and Sport Research 53 (2), 187-195, 2023
32023
Ingredient-based forecast of sold dish portions in campus canteen kitchens
L Woltmann, J Drechsel, C Hartmann, W Lehner
2022 IEEE 38th International Conference on Data Engineering Workshops (ICDEW …, 2022
32022
Large-Scale Time Series Analytics
M Hahmann, C Hartmann, L Kegel, W Lehner
Datenbank-Spektrum, 1-13, 2019
3*2019
Learned Selection Strategy for Lightweight Integer Compression Algorithms
L Woltmann, P Damme, C Hartmann, D Habich, W Lehner
Memory 3, 4, 2023
22023
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