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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
722019
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
212013
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
192015
Simplicity Done Right for Join Ordering
A Hertzschuch, C Hartmann, D Habich, W Lehner
CIDR, 2021
172021
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 (2), 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
72017
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
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
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
PostCENN: PostgreSQL with Machine Learning Models for Cardinality Estimation
L Woltmann, D Olwig, C Hartmann, D Habich, W Lehner
42021
Particulate Matter Matters—The Data Science Challenge@ BTW 2019
HJ Meyer, H Grunert, T Waizenegger, L Woltmann, C Hartmann, ...
Datenbank-Spektrum, 1-18, 2019
32019
Aggregate-based training phase for ML-based cardinality estimation
L Woltmann, C Hartmann, D Habich, W Lehner
Datenbank-Spektrum 22 (1), 45-57, 2022
22022
Season-and Trend-aware Symbolic Approximation for Accurate and Efficient Time Series Matching
L Kegel, C Hartmann, M Thiele, W Lehner
Datenbank-Spektrum 21 (3), 225-236, 2021
22021
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
22020
Forecasting Large-scale Time Series Data
C Hartmann
Technische Universität Dresden, 2018
22018
Feature-aware forecasting of large-scale time series data sets
C Hartmann, L Kegel, W Lehner
it-Information Technology, 2020
12020
Assessing the Impact of Driving Bans with Data Analysis
L Woltmann, C Hartmann, W Lehner
12019
Large-Scale Time Series Analytics
M Hahmann, C Hartmann, L Kegel, W Lehner
Datenbank-Spektrum, 1-13, 2019
12019
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
2022
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
2022
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