Sebastian Schelter

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 87

Top Venues

Technical University of Berlin, Germany (PHD)

Education History

Technical University of Berlin, Germany

PHD

Publications

Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang
Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. IEEE Data Eng. Bull. 47 (1) (2024)
Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang
Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR (2024)
Stefan Grafberger, Paul Groth, Sebastian Schelter
Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". DEEM@SIGMOD (2024)
Till Döhmen, Radu Geacu, Madelon Hulsebos, Sebastian Schelter
SchemaPile: A Large Collection of Relational Database Schemas. Proc. ACM Manag. Data 2 (3) (2024)
Sergey Redyuk, Zoi Kaoudi, Sebastian Schelter, Volker Markl
Assisted design of data science pipelines. VLDB J. 33 (4) (2024)
Barrie Kersbergen, Olivier Sprangers, Frank Kootte, Shubha Guha, Maarten de Rijke, Sebastian Schelter
Etude - Evaluating the Inference Latency of Session-Based Recommendation Models at Scale. ICDE (2024)
Songgaojun Deng, Olivier Sprangers, Ming Li, Sebastian Schelter, Maarten de Rijke
Domain Generalization in Time Series Forecasting. ACM Trans. Knowl. Discov. Data 18 (5) (2024)
Zeyu Zhang, Paul Groth, Iacer Calixto, Sebastian Schelter
Directions Towards Efficient and Automated Data Wrangling with Large Language Models. ICDEW (2024)
Stefan Grafberger, Paul Groth, Sebastian Schelter
Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". CoRR (2024)
Mozhdeh Ariannezhad, Ming Li, Sebastian Schelter, Maarten de Rijke
A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping. WSDM (2023)
Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang
Proactively Screening Machine Learning Pipelines with ARGUSEYES. SIGMOD Conference Companion (2023)
Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
On the Impact of Outlier Bias on User Clicks. SIGIR (2023)
Stefan Grafberger, Shubha Guha, Paul Groth, Sebastian Schelter
MLWHATIF: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over? Proc. VLDB Endow. 16 (12) (2023)
Xiaozhong Lyu, Stefan Grafberger, Samantha Biegel, Shaopeng Wei, Meng Cao, Sebastian Schelter, Ce Zhang
Improving Retrieval-Augmented Large Language Models via Data Importance Learning. CoRR (2023)
Olivier Sprangers, Wander Wadman, Sebastian Schelter, Maarten de Rijke
Hierarchical Forecasting at Scale. CoRR (2023)
Sebastian Schelter
Reconstructing and Querying ML Pipeline Intermediates. CIDR (2023)
Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, Sebastian Schelter
Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making. ICDE (2023)
Stefan Grafberger, Paul Groth, Sebastian Schelter
Provenance Tracking for End-to-End Machine Learning Pipelines. WWW (Companion Volume) (2023)
Fatemeh Sarvi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
How to Make an Outlier? Studying the Effect of Presentational Features on the Outlierness of Items in Product Search Results. CHIIR (2023)
Sebastian Schelter, Mozhdeh Ariannezhad, Maarten de Rijke
Forget Me Now: Fast and Exact Unlearning in Neighborhood-based Recommendation. SIGIR (2023)
Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
On the Impact of Outlier Bias on User Clicks. CoRR (2023)
Stefan Grafberger, Paul Groth, Sebastian Schelter
Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines. Proc. ACM Manag. Data 1 (2) (2023)
Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang
Screening Native Machine Learning Pipelines with ArgusEyes. CIDR (2022)
Stefan Grafberger, Paul Groth, Sebastian Schelter
Towards data-centric what-if analysis for native machine learning pipelines. DEEM@SIGMOD (2022)
Sebastian Schelter
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 45 (1) (2022)
Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, Sebastian Schelter
Responsible data management. Commun. ACM 65 (6) (2022)
Fatemeh Sarvi, Maria Heuss, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
Understanding and Mitigating the Effect of Outliers in Fair Ranking. WSDM (2022)
Benjamin Longxiang Wang, Sebastian Schelter
Efficiently Maintaining Next Basket Recommendations under Additions and Deletions of Baskets and Items. CoRR (2022)
Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang
Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR (2022)
Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter
Data distribution debugging in machine learning pipelines. VLDB J. 31 (5) (2022)
Till Döhmen, Madelon Hulsebos, Christian Beecks, Sebastian Schelter
GitSchemas: A Dataset for Automating Relational Data Preparation Tasks. ICDE Workshops (2022)
Mozhdeh Ariannezhad, Mohamed Yahya, Edgar Meij, Sebastian Schelter, Maarten de Rijke
Understanding Financial Information Seeking Behavior from User Interactions with Company Filings. WWW (Companion Volume) (2022)
Barrie Kersbergen, Olivier Sprangers, Sebastian Schelter
Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale. SIGMOD Conference (2022)
Sergey Redyuk, Zoi Kaoudi, Sebastian Schelter, Volker Markl
DORIAN in action: Assisted Design of Data Science Pipelines. Proc. VLDB Endow. 15 (12) (2022)
Mozhdeh Ariannezhad, Sami Jullien, Ming Li, Min Fang, Sebastian Schelter, Maarten de Rijke
ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping. SIGIR (2022)
Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. CoRR (2021)
Sebastian Schelter, Stefan Grafberger, Ted Dunning
HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning. SIGMOD Conference (2021)
Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter
Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. CIDR (2021)
Sergey Redyuk, Zoi Kaoudi, Volker Markl, Sebastian Schelter
Automating Data Quality Validation for Dynamic Data Ingestion. EDBT (2021)
Fatemeh Sarvi, Maria Heuss, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
Understanding and Mitigating the Effect of Outliers in Fair Ranking. CoRR (2021)
Sebastian Schelter, Tammo Rukat, Felix Biessmann
JENGA - A Framework to Study the Impact of Data Errors on the Predictions of Machine Learning Models. EDBT (2021)
Mozhdeh Ariannezhad, Sami Jullien, Pim Nauts, Min Fang, Sebastian Schelter, Maarten de Rijke
Understanding Multi-channel Customer Behavior in Retail. CIKM (2021)
Barrie Kersbergen, Sebastian Schelter
Learnings from a Retail Recommendation System on Billions of Interactions at bol.com. ICDE (2021)
Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. KDD (2021)
Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter
MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. SIGMOD Conference (2021)
Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
Parameter Efficient Deep Probabilistic Forecasting. CoRR (2021)
Sebastian Schelter
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 44 (1) (2021)
Sebastian Schelter
"Amnesia" - Machine Learning Models That Can Forget User Data Very Fast. CIDR (2020)
Robin Anil, Gökhan Çapan, Isabel Drost-Fromm, Ted Dunning, Ellen Friedman, Trevor Grant, Shannon Quinn, Paritosh Ranjan, Sebastian Schelter, Özgür Yilmazel
Apache Mahout: Machine Learning on Distributed Dataflow Systems. J. Mach. Learn. Res. 21 (2020)
Sebastian Schelter
Technical Perspective: Query Optimization for Faster Deep CNN Explanations. SIGMOD Rec. 49 (1) (2020)
Ji Zhang, Yuanzhang Wang, Yangtao Wang, Ke Zhou, Sebastian Schelter, Ping Huang, Bin Cheng, Yongguang Ji
Tier-Scrubbing: An Adaptive and Tiered Disk Scrubbing Scheme with Improved MTTD and Reduced Cost. DAC (2020)
Sebastian Schelter, Julia Stoyanovich
Taming Technical Bias in Machine Learning Pipelines. IEEE Data Eng. Bull. 43 (4) (2020)
Ji Zhang, Ping Huang, Ke Zhou, Ming Xie, Sebastian Schelter
HDDse: Enabling High-Dimensional Disk State Embedding for Generic Failure Detection System of Heterogeneous Disks in Large Data Centers. USENIX Annual Technical Conference (2020)
Sebastian Schelter
Three Challenges in Building Industrial-Scale Recommender Systems. ORSUM@RecSys (2020)
Mozhdeh Ariannezhad, Sebastian Schelter, Maarten de Rijke
Demand Forecasting in the Presence of Privileged Information. AALTD@PKDD/ECML (2020)
Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. EDBT (2020)
Fatemeh Sarvi, Nikos Voskarides, Lois Mooiman, Sebastian Schelter, Maarten de Rijke
A Comparison of Supervised Learning to Match Methods for Product Search. CoRR (2020)
Mariya Hendriksen, Ernst Kuiper, Pim Nauts, Sebastian Schelter, Maarten de Rijke
Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers. CoRR (2020)
Sergey Redyuk, Volker Markl, Sebastian Schelter
Towards Unsupervised Data Quality Validation on Dynamic Data. EDBT/ICDT Workshops (2020)
Amir Aghasadeghi, Vera Zaychik Moffitt, Sebastian Schelter, Julia Stoyanovich
Zooming Out on an Evolving Graph. EDBT (2020)
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
Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference (2020)
Sebastian Schelter, Tammo Rukat, Felix Bießmann
Learning to Validate the Predictions of Black Box Classifiers on Unseen Data. SIGMOD Conference (2020)
Sebastian Schelter, Stefan Grafberger, Philipp Schmidt, Tammo Rukat, Mario Kießling, Andrey Taptunov, Felix Bießmann, Dustin Lange
Differential Data Quality Verification on Partitioned Data. ICDE (2019)
Sebastian Schelter, Ufuk Celebi, Ted Dunning
Efficient Incremental Cooccurrence Analysis for Item-Based Collaborative Filtering. SSDBM (2019)
Sebastian Schelter, Felix Bießmann, Dustin Lange, Tammo Rukat, Philipp Schmidt, Stephan Seufert, Pierre Brunelle, Andrey Taptunov
Unit Testing Data with Deequ. SIGMOD Conference (2019)
Sergey Redyuk, Sebastian Schelter, Tammo Rukat, Volker Markl, Felix Bießmann
Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data. HILDA@SIGMOD (2019)
Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Sebastian Breß, Tilmann Rabl, Volker Markl
An Intermediate Representation for Optimizing Machine Learning Pipelines. Proc. VLDB Endow. 12 (11) (2019)
Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. CoRR (2019)
Sebastian Schelter, Neoklis Polyzotis, Manasi Vartak, Stephan Seufert
DEEM 2019: Workshop on Data Management for End-to-End Machine Learning. SIGMOD Conference (2019)
Tilmann Rabl, Christoph Brücke, Philipp Härtling, Stella Stars, Rodrigo Escobar Palacios, Hamesh Patel, Satyam Srivastava, Christoph Boden, Jens Meiners, Sebastian Schelter
ADABench - Towards an Industry Standard Benchmark for Advanced Analytics. TPCTC (2019)
Felix Bießmann, Tammo Rukat, Philipp Schmidt, Prathik Naidu, Sebastian Schelter, Andrey Taptunov, Dustin Lange, David Salinas
DataWig: Missing Value Imputation for Tables. J. Mach. Learn. Res. 20 (2019)
Sebastian Schelter, Jérôme Kunegis
On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl. J. Web Sci. 4 (4) (2018)
Sebastian Schelter, Dustin Lange, Philipp Schmidt, Meltem Celikel, Felix Bießmann, Andreas Grafberger
Automating Large-Scale Data Quality Verification. Proc. VLDB Endow. 11 (12) (2018)
Sebastian Schelter, Felix Bießmann, Tim Januschowski, David Salinas, Stephan Seufert, Gyuri Szarvas
On Challenges in Machine Learning Model Management. IEEE Data Eng. Bull. 41 (4) (2018)
Felix Bießmann, David Salinas, Sebastian Schelter, Philipp Schmidt, Dustin Lange
"Deep" Learning for Missing Value Imputationin Tables with Non-Numerical Data. CIKM (2018)
Christoph Boden, Tilmann Rabl, Sebastian Schelter, Volker Markl
Benchmarking Distributed Data Processing Systems for Machine Learning Workloads. TPCTC (2018)
Sebastian Schelter, Jérôme Kunegis
'Dark Germany': Temporal Characteristics and Connectivity Patterns in Online Far-Right Protests Against Refugee Housing. WebSci (2017)
Till Rohrmann, Sebastian Schelter, Tilmann Rabl, Volker Markl
Gilbert: Declarative Sparse Linear Algebra on Massively Parallel Dataflow Systems. BTW (2017)
Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang
Probabilistic Demand Forecasting at Scale. Proc. VLDB Endow. 10 (12) (2017)
Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Tilmann Rabl, Volker Markl
BlockJoin: Efficient Matrix Partitioning Through Joins. Proc. VLDB Endow. 10 (13) (2017)
Sebastian Schelter, Jérôme Kunegis
'Dark Germany': Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing. SocInfo (1) (2017)
Sebastian Schelter, Jérôme Kunegis
'Dark Germany': Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing. CoRR (2017)
Asterios Katsifodimos, Sebastian Schelter
Apache Flink: Stream Analytics at Scale. IC2E Workshops (2016)
Sebastian Schelter, Jérôme Kunegis
On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl. CoRR (2016)
Sebastian Schelter, Felix Bießmann, Malisa Zobel, Nedelina Teneva
Structural Patterns in the Rise of Germany's New Right on Facebook. ICDM Workshops (2016)
Nikolaas Steenbergen, Sebastian Schelter, Felix Bießmann
Doubly stochastic large scale kernel learning with the empirical kernel map. CoRR (2016)
Sebastian Schelter, Jérôme Kunegis
Tracking the Trackers: A Large-Scale Analysis of Embedded Web Trackers. ICWSM (2016)
Sebastian Schelter, Juan Soto, Volker Markl, Douglas Burdick, Berthold Reinwald, Alexandre V. Evfimievski
Efficient sample generation for scalable meta learning. ICDE (2015)
Sergey Dudoladov, Chen Xu, Sebastian Schelter, Asterios Katsifodimos, Stephan Ewen, Kostas Tzoumas, Volker Markl
Optimistic Recovery for Iterative Dataflows in Action. SIGMOD Conference (2015)
Sebastian Schelter
Scaling data mining in massively parallel dataflow systems. SIGMOD PhD Symposium (2014)
Sebastian Schelter, Venu Satuluri, Reza Zadeh
Factorbird - a Parameter Server Approach to Distributed Matrix Factorization. CoRR (2014)
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
The Stratosphere platform for big data analytics. VLDB J. 23 (6) (2014)
Stephan Ewen, Sebastian Schelter, Kostas Tzoumas, Daniel Warneke, Volker Markl
Iterative parallel data processing with stratosphere: an inside look. SIGMOD Conference (2013)
Sebastian Schelter, Stephan Ewen, Kostas Tzoumas, Volker Markl
"All roads lead to Rome": optimistic recovery for distributed iterative data processing. CIKM (2013)
Sebastian Schelter, Christoph Boden, Martin Schenck, Alexander Alexandrov, Volker Markl
Distributed matrix factorization with mapreduce using a series of broadcast-joins. RecSys (2013)
Sebastian Schelter, Christoph Boden, Volker Markl
Scalable similarity-based neighborhood methods with MapReduce. RecSys (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sebastian Schelter