Sebastian Schelter

126 papers A* 13A 13B 8Misc 1Journal 55Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Exploration. CoRR Chuangtao Ma, Zeyu Zhang, Arijit Khan, Sebastian Schelter, Paul Groth
2026	J	`jnl`	ERASE - A Real-World Aligned Benchmark for Unlearning in Recommender Systems. CoRR Pierre Lubitzsch, Maarten de Rijke, Sebastian Schelter
2026	J	`jnl`	SemPipes - Optimizable Semantic Data Operators for Tabular Machine Learning Pipelines. CoRR Olga Ovcharenko, Matthias Boehm, Sebastian Schelter
2026	J	`jnl`	stratum: A System Infrastructure for Massive Agent-Centric ML Workloads. CoRR Arnab Phani, Elias Strauss, Sebastian Schelter
2025	B	`conf`	A Deep Dive Into Cross-Dataset Entity Matching with Large and Small Language Models. EDBT Zeyu Zhang, Paul Groth, Iacer Calixto, Sebastian Schelter
2025	J	`jnl`	AmbiGraph-Eval: Can LLMs Effectively Handle Ambiguous Graph Queries? CoRR Yuchen Tian, Kaixin Li, Hao Chen, Ziyang Luo, Hongzhan Lin, Sebastian Schelter, Lun Du, Jing Ma
2025	A*	`conf`	Navigating Data Errors in Machine Learning Pipelines: Identify, Debug, and Learn. ICDE Bojan Karlas, Babak Salimi, Sebastian Schelter
2025	—	`conf`	Navigating Data Errors in Machine Learning Pipelines: Identify, Debug, and Learn. SIGMOD Conference Companion Bojan Karlas, Babak Salimi, Sebastian Schelter
2025	A	`conf`	Scalable Data Debugging for Neighborhood-based Recommendation with Data Shapley Values. RecSys Barrie Kersbergen, Olivier Sprangers, Bojan Karlas, Maarten de Rijke, Sebastian Schelter
2025	J	`jnl`	SemBench: A Benchmark for Semantic Query Processing Engines. CoRR Jiale Lao, Andreas Zimmerer, Olga Ovcharenko, Tianji Cong, Matthew Russo, Gerardo Vitagliano, Michael Cochez, Fatma Özcan, Gautam Gupta, Thibaud Hottelier, H. V. Jagadish, Kris Kissel, Sebastian Schelter, Andreas Kipf, Immanuel Trummer
2025	—	`conf`	Towards Automated Task-Aware Data Validation. DEEM@SIGMOD Hao Chen, Sebastian Schelter
2025	J	`jnl`	Towards Cross-Modal Error Detection with Tables and Images. CoRR Olga Ovcharenko, Sebastian Schelter
2025	—	`conf`	Towards Regaining Control Over Messy Machine Learning Pipelines. ICDEW Stefan Grafberger, Hao Chen, Olga Ovcharenko, Sebastian Schelter
2025	J	`jnl`	Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems. CoRR Pierre Lubitzsch, Olga Ovcharenko, Hao Chen, Maarten de Rijke, Sebastian Schelter
2025	J	`jnl`	Understanding Visual Saliency of Outlier Items in Product Search. CoRR Fatemeh Sarvi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
2025	J	`jnl`	mlidea: Interactively Improving ML Data Preparation Code via "Shadow Pipelines". Proc. VLDB Endow. Stefan Grafberger, Paul Groth, Sebastian Schelter
2025	A*	`conf`	scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data. ICML Olga Ovcharenko, Florian Barkmann, Philip Toma, Imant Daunhawer, Julia E. Vogt, Sebastian Schelter, Valentina Boeva
2025	J	`jnl`	scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data. CoRR Olga Ovcharenko, Florian Barkmann, Philip Toma, Imant Daunhawer, Julia E. Vogt, Sebastian Schelter, Valentina Boeva
2024	J	`jnl`	A Flexible Forecasting Stack. Proc. VLDB Endow. Tim Januschowski, Yuyang Wang, Jan Gasthaus, Syama Sundar Rangapuram, Caner Türkmen, Jasper Zschiegner, Lorenzo Stella, Michael Bohlke-Schneider, Danielle C. Maddix, Konstantinos Benidis, Alexander Alexandrov, Christos Faloutsos, Sebastian Schelter
2024	J	`jnl`	AnyMatch - Efficient Zero-Shot Entity Matching with a Small Language Model. CoRR Zeyu Zhang, Paul Groth, Iacer Calixto, Sebastian Schelter
2024	J	`jnl`	Assisted design of data science pipelines. VLDB J. Sergey Redyuk, Zoi Kaoudi, Sebastian Schelter, Volker Markl
2024	J	`jnl`	Automated Data Cleaning can Hurt Fairness in Machine Learning-Based Decision Making. IEEE Trans. Knowl. Data Eng. Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, Sebastian Schelter
2024	J	`jnl`	Automated Provenance-Based Screening of ML Data Preparation Pipelines. Datenbank-Spektrum Sebastian Schelter, Shubha Guha, Stefan Grafberger
2024	A*	`conf`	Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang
2024	—	`conf`	Directions Towards Efficient and Automated Data Wrangling with Large Language Models. ICDEW Zeyu Zhang, Paul Groth, Iacer Calixto, Sebastian Schelter
2024	J	`jnl`	Domain Generalization in Time Series Forecasting. ACM Trans. Knowl. Discov. Data Songgaojun Deng, Olivier Sprangers, Ming Li, Sebastian Schelter, Maarten de Rijke
2024	A*	`conf`	Etude - Evaluating the Inference Latency of Session-Based Recommendation Models at Scale. ICDE Barrie Kersbergen, Olivier Sprangers, Frank Kootte, Shubha Guha, Maarten de Rijke, Sebastian Schelter
2024	J	`jnl`	Messy Code Makes Managing ML Pipelines Difficult? Just Let LLMs Rewrite the Code! CoRR Sebastian Schelter, Stefan Grafberger
2024	J	`jnl`	Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. IEEE Data Eng. Bull. Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang
2024	J	`jnl`	SchemaPile: A Large Collection of Relational Database Schemas. Proc. ACM Manag. Data Till Döhmen, Radu Geacu, Madelon Hulsebos, Sebastian Schelter
2024	J	`jnl`	Snapcase - Regain Control over Your Predictions with Low-Latency Machine Unlearning. Proc. VLDB Endow. Sebastian Schelter, Stefan Grafberger, Maarten de Rijke
2024	—	`conf`	Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". DEEM@SIGMOD Stefan Grafberger, Paul Groth, Sebastian Schelter
2024	J	`jnl`	Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines". CoRR Stefan Grafberger, Paul Groth, Sebastian Schelter
2023	A	`conf`	A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping. WSDM Mozhdeh Ariannezhad, Ming Li, Sebastian Schelter, Maarten de Rijke
2023	A*	`conf`	Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making. ICDE Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, Sebastian Schelter
2023	J	`jnl`	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines. Proc. ACM Manag. Data Stefan Grafberger, Paul Groth, Sebastian Schelter
2023	A*	`conf`	Forget Me Now: Fast and Exact Unlearning in Neighborhood-based Recommendation. SIGIR Sebastian Schelter, Mozhdeh Ariannezhad, Maarten de Rijke
2023	J	`jnl`	Hierarchical Forecasting at Scale. CoRR Olivier Sprangers, Wander Wadman, Sebastian Schelter, Maarten de Rijke
2023	B	`conf`	How to Make an Outlier? Studying the Effect of Presentational Features on the Outlierness of Items in Product Search Results. CHIIR Fatemeh Sarvi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
2023	J	`jnl`	Improving Retrieval-Augmented Large Language Models via Data Importance Learning. CoRR Xiaozhong Lyu, Stefan Grafberger, Samantha Biegel, Shaopeng Wei, Meng Cao, Sebastian Schelter, Ce Zhang
2023	J	`jnl`	MLWHATIF: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over? Proc. VLDB Endow. Stefan Grafberger, Shubha Guha, Paul Groth, Sebastian Schelter
2023	A*	`conf`	On the Impact of Outlier Bias on User Clicks. SIGIR Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
2023	J	`jnl`	On the Impact of Outlier Bias on User Clicks. CoRR Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
2023	—	`conf`	Proactively Screening Machine Learning Pipelines with ARGUSEYES. SIGMOD Conference Companion Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang
2023	—	`conf`	Provenance Tracking for End-to-End Machine Learning Pipelines. WWW (Companion Volume) Stefan Grafberger, Paul Groth, Sebastian Schelter
2023	A	`conf`	Reconstructing and Querying ML Pipeline Intermediates. CIDR Sebastian Schelter
2022	J	`jnl`	DORIAN in action: Assisted Design of Data Science Pipelines. Proc. VLDB Endow. Sergey Redyuk, Zoi Kaoudi, Sebastian Schelter, Volker Markl
2022	J	`jnl`	Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang
2022	J	`jnl`	Data distribution debugging in machine learning pipelines. VLDB J. Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter
2022	J	`jnl`	Efficiently Maintaining Next Basket Recommendations under Additions and Deletions of Baskets and Items. CoRR Benjamin Longxiang Wang, Sebastian Schelter
2022	—	`conf`	GitSchemas: A Dataset for Automating Relational Data Preparation Tasks. ICDE Workshops Till Döhmen, Madelon Hulsebos, Christian Beecks, Sebastian Schelter
2022	J	`jnl`	Letter from the Special Issue Editor. IEEE Data Eng. Bull. Sebastian Schelter
2022	B	`ed.`	Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022, Edinburgh, UK, March 29 - April 1, 2022. EDBT Julia Stoyanovich, Jens Teubner, Paolo Guagliardo, Milos Nikolic, Andreas Pieris, Jan Mühlig, Fatma Özcan, Sebastian Schelter, H. V. Jagadish, Meihui Zhang
2022	A*	`conf`	ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping. SIGIR Mozhdeh Ariannezhad, Sami Jullien, Ming Li, Min Fang, Sebastian Schelter, Maarten de Rijke
2022	J	`jnl`	Responsible data management. Commun. ACM Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, Sebastian Schelter
2022	A	`conf`	Screening Native Machine Learning Pipelines with ArgusEyes. CIDR Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang
2022	—	`conf`	Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale. SIGMOD Conference Barrie Kersbergen, Olivier Sprangers, Sebastian Schelter
2022	—	`conf`	Towards data-centric what-if analysis for native machine learning pipelines. DEEM@SIGMOD Stefan Grafberger, Paul Groth, Sebastian Schelter
2022	—	`conf`	Understanding Financial Information Seeking Behavior from User Interactions with Company Filings. WWW (Companion Volume) Mozhdeh Ariannezhad, Mohamed Yahya, Edgar Meij, Sebastian Schelter, Maarten de Rijke
2022	A	`conf`	Understanding and Mitigating the Effect of Outliers in Fair Ranking. WSDM Fatemeh Sarvi, Maria Heuss, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
2021	B	`conf`	Automating Data Quality Validation for Dynamic Data Ingestion. EDBT Sergey Redyuk, Zoi Kaoudi, Volker Markl, Sebastian Schelter
2021	—	`conf`	HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning. SIGMOD Conference Sebastian Schelter, Stefan Grafberger, Ted Dunning
2021	B	`conf`	JENGA - A Framework to Study the Impact of Data Errors on the Predictions of Machine Learning Models. EDBT Sebastian Schelter, Tammo Rukat, Felix Biessmann
2021	A*	`conf`	Learnings from a Retail Recommendation System on Billions of Interactions at bol.com. ICDE Barrie Kersbergen, Sebastian Schelter
2021	J	`jnl`	Letter from the Special Issue Editor. IEEE Data Eng. Bull. Sebastian Schelter
2021	A	`conf`	Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. CIDR Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter
2021	—	`conf`	MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. SIGMOD Conference Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter
2021	J	`jnl`	Parameter Efficient Deep Probabilistic Forecasting. CoRR Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
2021	A*	`conf`	Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. KDD Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
2021	J	`jnl`	Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. CoRR Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
2021	A	`conf`	Understanding Multi-channel Customer Behavior in Retail. CIKM Mozhdeh Ariannezhad, Sami Jullien, Pim Nauts, Min Fang, Sebastian Schelter, Maarten de Rijke
2021	J	`jnl`	Understanding and Mitigating the Effect of Outliers in Fair Ranking. CoRR Fatemeh Sarvi, Maria Heuss, Mohammad Aliannejadi, Sebastian Schelter, Maarten de Rijke
2020	A	`conf`	"Amnesia" - Machine Learning Models That Can Forget User Data Very Fast. CIDR Sebastian Schelter
2020	J	`jnl`	A Comparison of Supervised Learning to Match Methods for Product Search. CoRR Fatemeh Sarvi, Nikos Voskarides, Lois Mooiman, Sebastian Schelter, Maarten de Rijke
2020	J	`jnl`	Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers. CoRR Mariya Hendriksen, Ernst Kuiper, Pim Nauts, Sebastian Schelter, Maarten de Rijke
2020	J	`jnl`	Apache Mahout: Machine Learning on Distributed Dataflow Systems. J. Mach. Learn. Res. Robin Anil, Gökhan Çapan, Isabel Drost-Fromm, Ted Dunning, Ellen Friedman, Trevor Grant, Shannon Quinn, Paritosh Ranjan, Sebastian Schelter, Özgür Yilmazel
2020	—	`conf`	Demand Forecasting in the Presence of Privileged Information. AALTD@PKDD/ECML Mozhdeh Ariannezhad, Sebastian Schelter, Maarten de Rijke
2020	—	`conf`	Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference 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
2020	B	`conf`	FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. EDBT Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
2020	—	`conf`	HDDse: Enabling High-Dimensional Disk State Embedding for Generic Failure Detection System of Heterogeneous Disks in Large Data Centers. USENIX ATC Ji Zhang, Ping Huang, Ke Zhou, Ming Xie, Sebastian Schelter
2020	—	`conf`	Learning to Validate the Predictions of Black Box Classifiers on Unseen Data. SIGMOD Conference Sebastian Schelter, Tammo Rukat, Felix Bießmann
2020	—	`ed.`	Proceedings of the Fourth Workshop on Data Management for End-To-End Machine Learning, In conjunction with the 2020 ACM SIGMOD/PODS Conference, DEEM@SIGMOD 2020, Portland, OR, USA, June 14, 2020 DEEM@SIGMOD Sebastian Schelter, Steven Whang, Julia Stoyanovich
2020	J	`jnl`	Taming Technical Bias in Machine Learning Pipelines. IEEE Data Eng. Bull. Sebastian Schelter, Julia Stoyanovich
2020	J	`jnl`	Technical Perspective: Query Optimization for Faster Deep CNN Explanations. SIGMOD Rec. Sebastian Schelter
2020	—	`conf`	Three Challenges in Building Industrial-Scale Recommender Systems. ORSUM@RecSys Sebastian Schelter
2020	A*	`conf`	Tier-Scrubbing: An Adaptive and Tiered Disk Scrubbing Scheme with Improved MTTD and Reduced Cost. DAC Ji Zhang, Yuanzhang Wang, Yangtao Wang, Ke Zhou, Sebastian Schelter, Ping Huang, Bin Cheng, Yongguang Ji
2020	—	`conf`	Towards Unsupervised Data Quality Validation on Dynamic Data. EDBT/ICDT Workshops Sergey Redyuk, Volker Markl, Sebastian Schelter
2020	B	`conf`	Zooming Out on an Evolving Graph. EDBT Amir Aghasadeghi, Vera Zaychik Moffitt, Sebastian Schelter, Julia Stoyanovich
2019	—	`conf`	ADABench - Towards an Industry Standard Benchmark for Advanced Analytics. TPCTC Tilmann Rabl, Christoph Brücke, Philipp Härtling, Stella Stars, Rodrigo Escobar Palacios, Hamesh Patel, Satyam Srivastava, Christoph Boden, Jens Meiners, Sebastian Schelter
2019	J	`jnl`	An Intermediate Representation for Optimizing Machine Learning Pipelines. Proc. VLDB Endow. Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Sebastian Breß, Tilmann Rabl, Volker Markl
2019	—	`conf`	DEEM 2019: Workshop on Data Management for End-to-End Machine Learning. SIGMOD Conference Sebastian Schelter, Neoklis Polyzotis, Manasi Vartak, Stephan Seufert
2019	J	`jnl`	DataWig: Missing Value Imputation for Tables. J. Mach. Learn. Res. Felix Bießmann, Tammo Rukat, Philipp Schmidt, Prathik Naidu, Sebastian Schelter, Andrey Taptunov, Dustin Lange, David Salinas
2019	A*	`conf`	Differential Data Quality Verification on Partitioned Data. ICDE Sebastian Schelter, Stefan Grafberger, Philipp Schmidt, Tammo Rukat, Mario Kießling, Andrey Taptunov, Felix Bießmann, Dustin Lange
2019	B	`conf`	Efficient Incremental Cooccurrence Analysis for Item-Based Collaborative Filtering. SSDBM Sebastian Schelter, Ufuk Celebi, Ted Dunning
2019	J	`jnl`	FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. CoRR Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
2019	—	`conf`	Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data. HILDA@SIGMOD Sergey Redyuk, Sebastian Schelter, Tammo Rukat, Volker Markl, Felix Bießmann
2019	—	`ed.`	Proceedings of the 3rd International Workshop on Data Management for End-to-End Machine Learning, DEEM@SIGMOD 2019, Amsterdam, The Netherlands, June 30, 2019 DEEM@SIGMOD Sebastian Schelter, Neoklis Polyzotis, Stephan Seufert, Manasi Vartak
2019	—	`conf`	Unit Testing Data with Deequ. SIGMOD Conference Sebastian Schelter, Felix Bießmann, Dustin Lange, Tammo Rukat, Philipp Schmidt, Stephan Seufert, Pierre Brunelle, Andrey Taptunov
2018	A	`conf`	"Deep" Learning for Missing Value Imputationin Tables with Non-Numerical Data. CIKM Felix Bießmann, David Salinas, Sebastian Schelter, Philipp Schmidt, Dustin Lange
2018	J	`jnl`	Automating Large-Scale Data Quality Verification. Proc. VLDB Endow. Sebastian Schelter, Dustin Lange, Philipp Schmidt, Meltem Celikel, Felix Bießmann, Andreas Grafberger
2018	—	`conf`	Benchmarking Distributed Data Processing Systems for Machine Learning Workloads. TPCTC Christoph Boden, Tilmann Rabl, Sebastian Schelter, Volker Markl
2018	J	`jnl`	On Challenges in Machine Learning Model Management. IEEE Data Eng. Bull. Sebastian Schelter, Felix Bießmann, Tim Januschowski, David Salinas, Stephan Seufert, Gyuri Szarvas
2018	J	`jnl`	On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl. J. Web Sci. Sebastian Schelter, Jérôme Kunegis
2018	—	`ed.`	Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, DEEM@SIGMOD 2018, Houston, TX, USA, June 15, 2018 DEEM@SIGMOD Sebastian Schelter, Stephan Seufert, Arun Kumar
2017	—	`conf`	'Dark Germany': Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing. SocInfo (1) Sebastian Schelter, Jérôme Kunegis
2017	J	`jnl`	'Dark Germany': Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing. CoRR Sebastian Schelter, Jérôme Kunegis
2017	—	`conf`	'Dark Germany': Temporal Characteristics and Connectivity Patterns in Online Far-Right Protests Against Refugee Housing. WebSci Sebastian Schelter, Jérôme Kunegis
2017	J	`jnl`	BlockJoin: Efficient Matrix Partitioning Through Joins. Proc. VLDB Endow. Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Tilmann Rabl, Volker Markl
2017	Misc	`conf`	Gilbert: Declarative Sparse Linear Algebra on Massively Parallel Dataflow Systems. BTW Till Rohrmann, Sebastian Schelter, Tilmann Rabl, Volker Markl
2017	J	`jnl`	Probabilistic Demand Forecasting at Scale. Proc. VLDB Endow. Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang
2017	—	`ed.`	Proceedings of the 1st Workshop on Data Management for End-to-End Machine Learning, DEEM@SIGMOD 2017, Chicago, IL, USA, May 14, 2017 DEEM@SIGMOD Sebastian Schelter, Reza Zadeh
2016	—	`conf`	Apache Flink: Stream Analytics at Scale. IC2E Workshops Asterios Katsifodimos, Sebastian Schelter
2016	J	`jnl`	Doubly stochastic large scale kernel learning with the empirical kernel map. CoRR Nikolaas Steenbergen, Sebastian Schelter, Felix Bießmann
2016	J	`jnl`	On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl. CoRR Sebastian Schelter, Jérôme Kunegis
2016	—	`—`	Scaling data mining in massively parallel dataflow systems. Sebastian Schelter
2016	—	`conf`	Structural Patterns in the Rise of Germany's New Right on Facebook. ICDM Workshops Sebastian Schelter, Felix Bießmann, Malisa Zobel, Nedelina Teneva
2016	A	`conf`	Tracking the Trackers: A Large-Scale Analysis of Embedded Web Trackers. ICWSM Sebastian Schelter, Jérôme Kunegis
2015	A*	`conf`	Efficient sample generation for scalable meta learning. ICDE Sebastian Schelter, Juan Soto, Volker Markl, Douglas Burdick, Berthold Reinwald, Alexandre V. Evfimievski
2015	—	`conf`	Optimistic Recovery for Iterative Dataflows in Action. SIGMOD Conference Sergey Dudoladov, Chen Xu, Sebastian Schelter, Asterios Katsifodimos, Stephan Ewen, Kostas Tzoumas, Volker Markl
2014	J	`jnl`	Factorbird - a Parameter Server Approach to Distributed Matrix Factorization. CoRR Sebastian Schelter, Venu Satuluri, Reza Zadeh
2014	—	`conf`	Scaling data mining in massively parallel dataflow systems. SIGMOD PhD Symposium Sebastian Schelter
2014	J	`jnl`	The Stratosphere platform for big data analytics. VLDB J. 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
2013	A	`conf`	"All roads lead to Rome": optimistic recovery for distributed iterative data processing. CIKM Sebastian Schelter, Stephan Ewen, Kostas Tzoumas, Volker Markl
2013	A	`conf`	Distributed matrix factorization with mapreduce using a series of broadcast-joins. RecSys Sebastian Schelter, Christoph Boden, Martin Schenck, Alexander Alexandrov, Volker Markl
2013	—	`conf`	Iterative parallel data processing with stratosphere: an inside look. SIGMOD Conference Stephan Ewen, Sebastian Schelter, Kostas Tzoumas, Daniel Warneke, Volker Markl
2012	A	`conf`	Scalable similarity-based neighborhood methods with MapReduce. RecSys Sebastian Schelter, Christoph Boden, Volker Markl