Követés
Sebastian Schelter
Sebastian Schelter
Professor at BIFOLD & TU Berlin
E-mail megerősítve itt: tu-berlin.de - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
The stratosphere platform for big data analytics
A Alexandrov, R Bergmann, S Ewen, JC Freytag, F Hueske, A Heise, ...
The VLDB Journal 23, 939-964, 2014
6622014
Automating large-scale data quality verification
S Schelter, D Lange, P Schmidt, M Celikel, F Biessmann, A Grafberger
Proceedings of the VLDB Endowment 11 (12), 1781-1794, 2018
2722018
On challenges in machine learning model management
S Schelter, F Biessmann, T Januschowski, D Salinas, S Seufert, ...
2332015
Probabilistic demand forecasting at scale
JH Böse, V Flunkert, J Gasthaus, T Januschowski, D Lange, D Salinas, ...
Proceedings of the VLDB Endowment 10 (12), 1694-1705, 2017
1812017
Automatically Tracking Metadata and Provenance of Machine Learning Experiments
S Schelter, JH Boese, J Kirschnick, T Klein, S Seufert
NIPS Workshop ML Systems, 2017
1712017
Elastic machine learning algorithms in amazon sagemaker
E Liberty, Z Karnin, B Xiang, L Rouesnel, B Coskun, R Nallapati, ...
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
1452020
DataWig: Missing value imputation for tables
F Biessmann, T Rukat, P Schmidt, P Naidu, S Schelter, A Taptunov, ...
Journal of Machine Learning Research 20 (175), 1-6, 2019
1212019
Hedgecut: Maintaining randomised trees for low-latency machine unlearning
S Schelter, S Grafberger, T Dunning
Proceedings of the 2021 International Conference on Management of Data, 1545 …, 2021
952021
Deep Learning for Missing Value Imputation in Tables with Non-Numerical Data
F Biessmann, D Salinas, S Schelter, P Schmidt, D Lange
Proceedings of the 27th ACM International Conference on Information and …, 2018
942018
Scalable similarity-based neighborhood methods with mapreduce
S Schelter, C Boden, V Markl
Proceedings of the sixth ACM conference on Recommender systems, 163-170, 2012
832012
"All roads lead to Rome": Optimistic recovery for distributed iterative data processing
S Schelter, S Ewen, K Tzoumas, V Markl
Proceedings of the 22nd ACM international conference on Information …, 2013
722013
An intermediate representation for optimizing machine learning pipelines
A Kunft, A Katsifodimos, S Schelter, S Breß, T Rabl, V Markl
Proceedings of the VLDB Endowment 12 (11), 1553-1567, 2019
672019
Collaborative filtering with apache mahout
S Schelter, S Owen
Proc. of ACM RecSys challenge, 2012
672012
Distributed matrix factorization with mapreduce using a series of broadcast-joins
S Schelter, C Boden, M Schenck, A Alexandrov, V Markl
Proceedings of the 7th ACM Conference on Recommender Systems, 281-284, 2013
652013
Fairprep: Promoting data to a first-class citizen in studies on fairness-enhancing interventions
S Schelter, Y He, J Khilnani, J Stoyanovich
arXiv preprint arXiv:1911.12587, 2019
642019
ReCANet: A repeat consumption-aware neural network for next basket recommendation in grocery shopping
M Ariannezhad, S Jullien, M Li, M Fang, S Schelter, M De Rijke
Proceedings of the 45th international ACM SIGIR conference on research and …, 2022
612022
Learning to validate the predictions of black box classifiers on unseen data
S Schelter, T Rukat, F Bießmann
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
502020
Apache mahout: Machine learning on distributed dataflow systems
R Anil, G Capan, I Drost-Fromm, T Dunning, E Friedman, T Grant, S Quinn, ...
Journal of Machine Learning Research 21 (127), 1-6, 2020
502020
On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl
S Schelter, J Kunegis
Journal of Web Science 4 (4), 53-66, 2018
502018
Fairness-Aware Instrumentation of Preprocessing~ Pipelines for Machine Learning
K Yang, B Huang, J Stoyanovich, S Schelter
Workshop on Human-In-the-Loop Data Analytics (HILDA'20), 2020
482020
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Cikkek 1–20