Sebastian Schelter

According to our database, Sebastian Schelter authored at least 82 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI.

Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang

IEEE Data Eng. Bull., 2024

2023

MLWHATIF: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over?

Stefan Grafberger, Shubha Guha, Paul Groth, Sebastian Schelter

Proc. VLDB Endow., 2023

Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines.

Stefan Grafberger, Paul Groth, Sebastian Schelter

Proc. ACM Manag. Data, 2023

Hierarchical Forecasting at Scale.

Olivier Sprangers, Wander Wadman, Sebastian Schelter, Maarten de Rijke

CoRR, 2023

Improving Retrieval-Augmented Large Language Models via Data Importance Learning.

Xiaozhong Lyu, Stefan Grafberger, Samantha Biegel, Shaopeng Wei, Meng Cao, Sebastian Schelter, Ce Zhang

CoRR, 2023

Provenance Tracking for End-to-End Machine Learning Pipelines.

Stefan Grafberger, Paul Groth, Sebastian Schelter

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping.

Mozhdeh Ariannezhad, Ming Li, Sebastian Schelter, Maarten de Rijke

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Proactively Screening Machine Learning Pipelines with ARGUSEYES.

Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

Forget Me Now: Fast and Exact Unlearning in Neighborhood-based Recommendation.

Sebastian Schelter, Mozhdeh Ariannezhad, Maarten de Rijke

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

On the Impact of Outlier Bias on User Clicks.

Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making.

Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, Sebastian Schelter

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Reconstructing and Querying ML Pipeline Intermediates.

Sebastian Schelter

Proceedings of the 13th Conference on Innovative Data Systems Research, 2023

How to Make an Outlier? Studying the Effect of Presentational Features on the Outlierness of Items in Product Search Results.

Fatemeh Sarvi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke

Proceedings of the 2023 Conference on Human Information Interaction and Retrieval, 2023

2022

Data distribution debugging in machine learning pipelines.

Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter

VLDB J., 2022

DORIAN in action: Assisted Design of Data Science Pipelines.

Sergey Redyuk, Zoi Kaoudi, Sebastian Schelter, Volker Markl

Proc. VLDB Endow., 2022

Letter from the Special Issue Editor.

Sebastian Schelter

IEEE Data Eng. Bull., 2022

Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines.

Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang

CoRR, 2022

Efficiently Maintaining Next Basket Recommendations under Additions and Deletions of Baskets and Items.

Benjamin Longxiang Wang, Sebastian Schelter

CoRR, 2022

Responsible data management.

Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, Sebastian Schelter

Commun. ACM, 2022

Understanding Financial Information Seeking Behavior from User Interactions with Company Filings.

Mozhdeh Ariannezhad, Mohamed Yahya, Edgar Meij, Sebastian Schelter, Maarten de Rijke

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Understanding and Mitigating the Effect of Outliers in Fair Ranking.

Fatemeh Sarvi, Maria Heuss, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale.

Barrie Kersbergen, Olivier Sprangers, Sebastian Schelter

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping.

Mozhdeh Ariannezhad, Sami Jullien, Ming Li, Min Fang, Sebastian Schelter, Maarten de Rijke

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

GitSchemas: A Dataset for Automating Relational Data Preparation Tasks.

Till Döhmen, Madelon Hulsebos, Christian Beecks, Sebastian Schelter

Proceedings of the 38th IEEE International Conference on Data Engineering Workshops, 2022

Towards data-centric what-if analysis for native machine learning pipelines.

Stefan Grafberger, Paul Groth, Sebastian Schelter

Proceedings of the DEEM '22: Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning Philadelphia, 2022

Screening Native Machine Learning Pipelines with ArgusEyes.

Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang

Proceedings of the 12th Conference on Innovative Data Systems Research, 2022

2021

Parameter Efficient Deep Probabilistic Forecasting.

Olivier Sprangers, Sebastian Schelter, Maarten de Rijke

CoRR, 2021

HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning.

Sebastian Schelter, Stefan Grafberger, Ted Dunning

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines.

Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression.

Olivier Sprangers, Sebastian Schelter, Maarten de Rijke

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Learnings from a Retail Recommendation System on Billions of Interactions at bol.com.

Barrie Kersbergen, Sebastian Schelter

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

JENGA - A Framework to Study the Impact of Data Errors on the Predictions of Machine Learning Models.

Sebastian Schelter, Tammo Rukat, Felix Biessmann

Proceedings of the 24th International Conference on Extending Database Technology, 2021

Automating Data Quality Validation for Dynamic Data Ingestion.

Sergey Redyuk, Zoi Kaoudi, Volker Markl, Sebastian Schelter

Proceedings of the 24th International Conference on Extending Database Technology, 2021

Understanding Multi-channel Customer Behavior in Retail.

Mozhdeh Ariannezhad, Sami Jullien, Pim Nauts, Min Fang, Sebastian Schelter, Maarten de Rijke

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines.

Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2020

Technical Perspective: Query Optimization for Faster Deep CNN Explanations.

Sebastian Schelter

SIGMOD Rec., 2020

Apache Mahout: Machine Learning on Distributed Dataflow Systems.

Robin Anil, Gökhan Çapan, Isabel Drost-Fromm, Ted Dunning, Ellen Friedman, Trevor Grant, Shannon Quinn, Paritosh Ranjan, Sebastian Schelter, Özgür Yilmazel

J. Mach. Learn. Res., 2020

Taming Technical Bias in Machine Learning Pipelines.

Sebastian Schelter, Julia Stoyanovich

IEEE Data Eng. Bull., 2020

Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers.

Mariya Hendriksen, Ernst Kuiper, Pim Nauts, Sebastian Schelter, Maarten de Rijke

CoRR, 2020

A Comparison of Supervised Learning to Match Methods for Product Search.

Fatemeh Sarvi, Nikos Voskarides, Lois Mooiman, Sebastian Schelter, Maarten de Rijke

CoRR, 2020

HDDse: Enabling High-Dimensional Disk State Embedding for Generic Failure Detection System of Heterogeneous Disks in Large Data Centers.

Ji Zhang, Ping Huang, Ke Zhou, Ming Xie, Sebastian Schelter

Proceedings of the 2020 USENIX Annual Technical Conference, 2020

Learning to Validate the Predictions of Black Box Classifiers on Unseen Data.

Sebastian Schelter, Tammo Rukat, Felix Bießmann

Proceedings of the 2020 International Conference on Management of Data, 2020

Elastic Machine Learning Algorithms in Amazon SageMaker.

Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola

Proceedings of the 2020 International Conference on Management of Data, 2020

Three Challenges in Building Industrial-Scale Recommender Systems.

Sebastian Schelter

Proceedings of the 3rd Workshop on Online Recommender Systems and User Modeling co-located with the 14th ACM Conference on Recommender Systems (RecSys 2020), 2020

Demand Forecasting in the Presence of Privileged Information.

Mozhdeh Ariannezhad, Sebastian Schelter, Maarten de Rijke

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2020

FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions.

Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich

Proceedings of the 23rd International Conference on Extending Database Technology, 2020

Towards Unsupervised Data Quality Validation on Dynamic Data.

Sergey Redyuk, Volker Markl, Sebastian Schelter

Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, 2020

Zooming Out on an Evolving Graph.

Amir Aghasadeghi, Vera Zaychik Moffitt, Sebastian Schelter, Julia Stoyanovich

Proceedings of the 23rd International Conference on Extending Database Technology, 2020

Tier-Scrubbing: An Adaptive and Tiered Disk Scrubbing Scheme with Improved MTTD and Reduced Cost.

Ji Zhang, Yuanzhang Wang, Yangtao Wang, Ke Zhou, Sebastian Schelter, Ping Huang, Bin Cheng, Yongguang Ji

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

"Amnesia" - Machine Learning Models That Can Forget User Data Very Fast.

Sebastian Schelter

Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019

An Intermediate Representation for Optimizing Machine Learning Pipelines.

Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Sebastian Breß, Tilmann Rabl, Volker Markl

Proc. VLDB Endow., 2019

DataWig: Missing Value Imputation for Tables.

Felix Bießmann, Tammo Rukat, Philipp Schmidt, Prathik Naidu, Sebastian Schelter, Andrey Taptunov, Dustin Lange, David Salinas

J. Mach. Learn. Res., 2019

ADABench - Towards an Industry Standard Benchmark for Advanced Analytics.

Tilmann Rabl, Christoph Brücke, Philipp Härtling, Stella Stars, Rodrigo Escobar Palacios, Hamesh Patel, Satyam Srivastava, Christoph Boden, Jens Meiners, Sebastian Schelter

Proceedings of the Performance Evaluation and Benchmarking for the Era of Cloud(s), 2019

Efficient Incremental Cooccurrence Analysis for Item-Based Collaborative Filtering.

Sebastian Schelter, Ufuk Celebi, Ted Dunning

Proceedings of the 31st International Conference on Scientific and Statistical Database Management, 2019

DEEM 2019: Workshop on Data Management for End-to-End Machine Learning.

Sebastian Schelter, Neoklis Polyzotis, Manasi Vartak, Stephan Seufert

Proceedings of the 2019 International Conference on Management of Data, 2019

Unit Testing Data with Deequ.

Sebastian Schelter, Felix Bießmann, Dustin Lange, Tammo Rukat, Philipp Schmidt, Stephan Seufert, Pierre Brunelle, Andrey Taptunov

Proceedings of the 2019 International Conference on Management of Data, 2019

Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data.

Sergey Redyuk, Sebastian Schelter, Tammo Rukat, Volker Markl, Felix Bießmann

Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2019

Differential Data Quality Verification on Partitioned Data.

Sebastian Schelter, Stefan Grafberger, Philipp Schmidt, Tammo Rukat, Mario Kießling, Andrey Taptunov, Felix Bießmann, Dustin Lange

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

2018

Automating Large-Scale Data Quality Verification.

Sebastian Schelter, Dustin Lange, Philipp Schmidt, Meltem Celikel, Felix Bießmann, Andreas Grafberger

Proc. VLDB Endow., 2018

On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl.

Sebastian Schelter, Jérôme Kunegis

J. Web Sci., 2018

On Challenges in Machine Learning Model Management.

Sebastian Schelter, Felix Bießmann, Tim Januschowski, David Salinas, Stephan Seufert, Gyuri Szarvas

IEEE Data Eng. Bull., 2018

Benchmarking Distributed Data Processing Systems for Machine Learning Workloads.

Christoph Boden, Tilmann Rabl, Sebastian Schelter, Volker Markl

Proceedings of the Performance Evaluation and Benchmarking for the Era of Artificial Intelligence, 2018

"Deep" Learning for Missing Value Imputationin Tables with Non-Numerical Data.

Felix Bießmann, David Salinas, Sebastian Schelter, Philipp Schmidt, Dustin Lange

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

BlockJoin: Efficient Matrix Partitioning Through Joins.

Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Tilmann Rabl, Volker Markl

Proc. VLDB Endow., 2017

Probabilistic Demand Forecasting at Scale.

Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang

Proc. VLDB Endow., 2017

'Dark Germany': Temporal Characteristics and Connectivity Patterns in Online Far-Right Protests Against Refugee Housing.

Sebastian Schelter, Jérôme Kunegis

Proceedings of the 2017 ACM on Web Science Conference, 2017

'Dark Germany': Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing.

Sebastian Schelter, Jérôme Kunegis

Proceedings of the Social Informatics, 2017

Gilbert: Declarative Sparse Linear Algebra on Massively Parallel Dataflow Systems.

Till Rohrmann, Sebastian Schelter, Tilmann Rabl, Volker Markl

Proceedings of the Datenbanksysteme für Business, 2017

2016

Scaling data mining in massively parallel dataflow systems.

Sebastian Schelter

PhD thesis, 2016

Doubly stochastic large scale kernel learning with the empirical kernel map.

Nikolaas Steenbergen, Sebastian Schelter, Felix Bießmann

CoRR, 2016

Tracking the Trackers: A Large-Scale Analysis of Embedded Web Trackers.

Sebastian Schelter, Jérôme Kunegis

Proceedings of the Tenth International Conference on Web and Social Media, 2016

Structural Patterns in the Rise of Germany's New Right on Facebook.

Sebastian Schelter, Felix Bießmann, Malisa Zobel, Nedelina Teneva

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Apache Flink: Stream Analytics at Scale.

Asterios Katsifodimos, Sebastian Schelter

Proceedings of the 2016 IEEE International Conference on Cloud Engineering Workshop, 2016

2015

Optimistic Recovery for Iterative Dataflows in Action.

Sergey Dudoladov, Chen Xu, Sebastian Schelter, Asterios Katsifodimos, Stephan Ewen, Kostas Tzoumas, Volker Markl

Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015

Efficient sample generation for scalable meta learning.

Sebastian Schelter, Juan Soto, Volker Markl, Douglas Burdick, Berthold Reinwald, Alexandre V. Evfimievski

Proceedings of the 31st IEEE International Conference on Data Engineering, 2015

2014

The Stratosphere platform for big data analytics.

Alexander Alexandrov, Rico Bergmann, Stephan Ewen, Johann-Christoph Freytag, Fabian Hueske, Arvid Heise, Odej Kao, Marcus Leich, Ulf Leser, Volker Markl, Felix Naumann, Mathias Peters, Astrid Rheinländer, Matthias J. Sax, Sebastian Schelter, Mareike Höger, Kostas Tzoumas, Daniel Warneke

VLDB J., 2014

Factorbird - a Parameter Server Approach to Distributed Matrix Factorization.

Sebastian Schelter, Venu Satuluri, Reza Zadeh

CoRR, 2014

Scaling data mining in massively parallel dataflow systems.

Sebastian Schelter

Proceedings of the International Conference on Management of Data, 2014

2013

Iterative parallel data processing with stratosphere: an inside look.

Stephan Ewen, Sebastian Schelter, Kostas Tzoumas, Daniel Warneke, Volker Markl

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

Distributed matrix factorization with mapreduce using a series of broadcast-joins.

Sebastian Schelter, Christoph Boden, Martin Schenck, Alexander Alexandrov, Volker Markl

Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

"All roads lead to Rome": optimistic recovery for distributed iterative data processing.

Sebastian Schelter, Stephan Ewen, Kostas Tzoumas, Volker Markl

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012

Scalable similarity-based neighborhood methods with MapReduce.

Sebastian Schelter, Christoph Boden, Volker Markl

Proceedings of the Sixth ACM Conference on Recommender Systems, 2012