Matthias Boehm
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
31
Venues
11
Active years
2011–2026
Best venue rank
A*
Where they publish
Papers
31 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EDBT | CAMEO: Autocorrelation-Preserving Line Simplification for Lossy Time Series Compression. | Carlos Enrique Muiz-Cuza, Matthias Boehm, Torben Bach Pedersen |
| 2026 | EDBT | TerseTS: A Framework for Time Series Compression. | Carlos Enrique Muiz-Cuza, Sren Kejser Jensen, Tom Louis Klein, Sabina Bakhtiiarova, Matthias Boehm, Torben Bach Pedersen |
| 2026 | EDBT | MetricLib: A Modular and Extensible Toolkit for Evaluation of Medical ML Datasets. | Martin Seyferth, Katinka Becker, Tobias Schaeffter, Daniel Schwabe, Matthias Boehm |
| 2025 | BTW | Fast, Parameter-free Time Series Anomaly Detection. | Kristiyan Blagov, Carlos Enrique Muiz-Cuza, Matthias Boehm |
| 2025 | BTW | Scalable Computation of Shapley Additive Explanations. | Louis Le Page, Christina Dionysio, Matthias Boehm |
| 2025 | BTW | Incremental SliceLine for Iterative ML Model Debugging under Updates. | Frederic Caspar Zoepffel, Christina Dionysio, Matthias Boehm |
| 2025 | EDBT | MEMPHIS: Holistic Lineage-based Reuse and Memory Management for Multi-backend ML Systems. | Arnab Phani, Matthias Boehm |
| 2025 | SIGMOD | Demonstrating CatDB: LLM-based Generation of Data-centric ML Pipelines. | Saeed Fathollahzadeh, Essam Mansour, Matthias Boehm |
| 2025 | VLDB | Learning to Accelerate: Tuning Data Transfer Parameters. | Benedikt Didrich, Haralampos Gavriilidis, Vasilis Gkolemis, Matthias Boehm, Volker Markl |
| 2025 | VLDB | Composability and Interoperability for Federated Data Systems. | Haralampos Gavriilidis, Leonhard Rose, Joel Ziegler, Jonathan Gerloff, Benedikt Didrich, Midhun Kaippillil Venugopalan, Kaustubh Beedkar, Matthias Boehm, Volker Markl |
| 2024 | SIGMOD | PLUTUS: Understanding Data Distribution Tailoring for Machine Learning. | Jiwon Chang, Christina Dionysio, Fatemeh Nargesian, Matthias Boehm |
| 2023 | BTW | Enabling Integrated Data Analysis Pipelines on Heterogeneous Hardware through Holistic Extensibility. | Patrick Damme, Matthias Boehm |
| 2023 | EuroPar | DAPHNE Runtime: Harnessing Parallelism for Integrated Data Analysis Pipelines. | Aristotelis Vontzalidis, Stratos Psomadakis, Constantinos Bitsakos, Mark Dokter, Kevin Innerebner, Patrick Damme, Matthias Boehm, Florina M. Ciorba, Ahmed Eleliemy, Vasileios Karakostas, Ales Zamuda, Dimitrios Tsoumakos |
| 2023 | SIGMOD | Seventh Workshop on Data Management for End-to-End Machine Learning (DEEM). | Matthias Boehm, Madelon Hulsebos, Shreya Shankar, Paroma Varma |
| 2023 | SIGMOD | Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques. | Matthias Boehm, Matteo Interlandi, Chris Jermaine |
| 2022 | CIDR | DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines. | Patrick Damme, Marius Birkenbach, Constantinos Bitsakos, Matthias Boehm, Philippe Bonnet, Florina M. Ciorba, Mark Dokter, Pawel Dowgiallo, Ahmed Eleliemy, Christian Faerber, Georgios I. Goumas, Dirk Habich, Niclas Hedam, Marlies Hofer, Wenjun Huang, Kevin Innerebner, Vasileios Karakostas, Roman Kern, Tomaz Kosar, Alexander Krause, Daniel Krems, Andreas Laber, Wolfgang Lehner, Eric Mier, Marcus Paradies, Bernhard Peischl, Gabrielle Poerwawinata, Stratos Psomadakis, Tilmann Rabl, Piotr Ratuszniak, Pedro Silva, Nikolai Skuppin, Andreas Starzacher, Benjamin Steinwender, Ilin Tolovski, Pinar Tzn, Wojciech Ulatowski, Yuanyuan Wang, Izajasz P. Wrosz, Ales Zamuda, Ce Zhang, Xiaoxiang Zhu |
| 2022 | CIKM | Federated Data Preparation, Learning, and Debugging in Apache SystemDS. | Sebastian Baunsgaard, Matthias Boehm, Kevin Innerebner, Mito Kehayov, Florian Lackner, Olga Ovcharenko, Arnab Phani, Tobias Rieger, David Weissteiner, Sebastian Benjamin Wrede |
| 2022 | SIGMOD | DEEM'22: Data Management for End-to-End Machine Learning. | Matthias Boehm, Paroma Varma, Doris Xin |
| 2021 | SIGMOD | ExDRa: Exploratory Data Science on Federated Raw Data. | Sebastian Baunsgaard, Matthias Boehm, Ankit Chaudhary, Behrouz Derakhshan, Stefan Geielsder, Philipp M. Grulich, Michael Hildebrand, Kevin Innerebner, Volker Markl, Claus Neubauer, Sarah Osterburg, Olga Ovcharenko, Sergey Redyuk, Tobias Rieger, Alireza Rezaei Mahdiraji, Sebastian Benjamin Wrede, Steffen Zeuch |
| 2021 | SIGMOD | LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems. | Arnab Phani, Benjamin Rath, Matthias Boehm |
| 2021 | SIGMOD | SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging. | Svetlana Sagadeeva, Matthias Boehm |
| 2020 | CIDR | SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle. | Matthias Boehm, Iulian Antonov, Sebastian Baunsgaard, Mark Dokter, Robert Ginthr, Kevin Innerebner, Florijan Klezin, Stefanie N. Lindstaedt, Arnab Phani, Benjamin Rath, Berthold Reinwald, Shafaq Siddiqui, Sebastian Benjamin Wrede |
| 2020 | EMNLP | Learning Explainable Linguistic Expressions with Neural Inductive Logic Programming for Sentence Classification. | Prithviraj Sen, Marina Danilevsky, Yunyao Li, Siddhartha Brahma, Matthias Boehm, Laura Chiticariu, Rajasekar Krishnamurthy |
| 2019 | BTW | Efficient Data-Parallel Cumulative Aggregates for Large-Scale Machine Learning. | Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald |
| 2019 | SIGMOD | MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions. | Johanna Sommer, Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald, Peter J. Haas |
| 2017 | CIDR | SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning. | Tarek Elgamal, Shangyu Luo, Matthias Boehm, Alexandre V. Evfimievski, Shirish Tatikonda, Berthold Reinwald, Prithviraj Sen |
| 2017 | SIGMOD | Data Management in Machine Learning: Challenges, Techniques, and Systems. | Arun Kumar, Matthias Boehm, Jun Yang |
| 2015 | PPoPP | On optimizing machine learning workloads via kernel fusion. | Arash Ashari, Shirish Tatikonda, Matthias Boehm, Berthold Reinwald, Keith Campbell, John Keenleyside, P. Sadayappan |
| 2015 | SIGMOD | Resource Elasticity for Large-Scale Machine Learning. | Botong Huang, Matthias Boehm, Yuanyuan Tian, Berthold Reinwald, Shirish Tatikonda, Frederick R. Reiss |
| 2013 | CLOUD | Compiling machine learning algorithms with SystemML. | Matthias Boehm, Douglas Burdick, Alexandre V. Evfimievski, Berthold Reinwald, Prithviraj Sen, Shirish Tatikonda, Yuanyuan Tian |
| 2011 | GI | Berufsbegleitende weiterbildung im spannungsfeld von wissenschaft und IT-beratung: state-of-the-art und entwicklung eines vorgehensmodells. | Matthias Boehm, Carl Stolze, Oliver Thomas |