Matthias Boehm

According to our database, Matthias Boehm authored at least 77 papers between 2007 and 2024.

Collaborative distances:

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

2024

Special issue on "Machine learning and databases".

Matthias Boehm, Nesime Tatbul

VLDB J., July, 2024

POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance.

David Justen, Daniel Ritter, Campbell Fraser, Andrew Lamb, Nga Tran, Allison Lee, Thomas Bodner, Mhd Yamen Haddad, Steffen Zeuch, Volker Markl, Matthias Boehm

Proc. VLDB Endow., February, 2024

PLUTUS: Understanding Data Distribution Tailoring for Machine Learning.

Jiwon Chang, Christina Dionysio, Fatemeh Nargesian, Matthias Boehm

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

2023

SAGA: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications.

Shafaq Siddiqi, Roman Kern, Matthias Boehm

Proc. ACM Manag. Data, September, 2023

Front Matter.

Georgia Koutrika, Jun Yang, Manos Athanassoulis, Kostas Stefanidis, Ju Fan, Abdul Quamar, Yuanyan Tian, Alekh Jindal, Carsten Binnig, Jennie Rogers, Senjuti Basu Roy, Steven Euijong Whang, Matthias Boehm, Aaron J. Elmore, Vasilis Efthymiou, Xiao Hu, Xiaofang Zhou, Alan D. Fekete

Proc. VLDB Endow., 2023

GIO: Generating Efficient Matrix and Frame Readers for Custom Data Formats by Example.

Saeed Fathollahzadeh, Matthias Boehm

Proc. ACM Manag. Data, 2023

AWARE: Workload-aware, Redundancy-exploiting Linear Algebra.

Sebastian Baunsgaard, Matthias Boehm

Proc. ACM Manag. Data, 2023

Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques.

Matthias Boehm, Matteo Interlandi, Chris Jermaine

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

Seventh Workshop on Data Management for End-to-End Machine Learning (DEEM).

Matthias Boehm, Madelon Hulsebos, Shreya Shankar, Paroma Varma

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

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

Proceedings of the Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28, 2023

A Tutorial Workshop on ML for Systems and Systems for ML.

Manisha Luthra, Andreas Kipf, Matthias Böhm

Proceedings of the Datenbanksysteme für Business, 2023

Enabling Integrated Data Analysis Pipelines on Heterogeneous Hardware through Holistic Extensibility.

Patrick Damme, Matthias Boehm

Proceedings of the Datenbanksysteme für Business, 2023

2022

UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads.

Arnab Phani, Lukas Erlbacher, Matthias Boehm

Proc. VLDB Endow., 2022

DEEM'22: Data Management for End-to-End Machine Learning.

Matthias Boehm, Paroma Varma, Doris Xin

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

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

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

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 Tözün, Wojciech Ulatowski, Yuanyuan Wang, Izajasz P. Wrosz, Ales Zamuda, Ce Zhang, Xiaoxiang Zhu

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

2021

SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging.

Svetlana Sagadeeva, Matthias Boehm

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

LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems.

Arnab Phani, Benjamin Rath, Matthias Boehm

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

ExDRa: Exploratory Data Science on Federated Raw Data.

Sebastian Baunsgaard, Matthias Boehm, Ankit Chaudhary, Behrouz Derakhshan, Stefan Geißelsöder, 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

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

2020

Technical Perspective: Declarative Recursive Computation on an RDBMS.

Matthias Boehm

SIGMOD Rec., 2020

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

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle.

Matthias Boehm, Iulian Antonov, Sebastian Baunsgaard, Mark Dokter, Robert Ginthör, Kevin Innerebner, Florijan Klezin, Stefanie N. Lindstaedt, Arnab Phani, Benjamin Rath, Berthold Reinwald, Shafaq Siddiqui, Sebastian Benjamin Wrede

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

2019

Data Management in Machine Learning Systems

Matthias Boehm, Arun Kumar, Jun Yang

Synthesis Lectures on Data Management, Morgan & Claypool Publishers, ISBN: 978-3-031-01869-5, 2019

Apache SystemML.

Matthias Boehm

Proceedings of the Encyclopedia of Big Data Technologies., 2019

SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle.

Matthias Boehm, Iulian Antonov, Mark Dokter, Robert Ginthör, Kevin Innerebner, Florijan Klezin, Stefanie N. Lindstaedt, Arnab Phani, Benjamin Rath

CoRR, 2019

Compressed linear algebra for declarative large-scale machine learning.

Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald

Commun. ACM, 2019

MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions.

Johanna Sommer, Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald, Peter J. Haas

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

Efficient Data-Parallel Cumulative Aggregates for Large-Scale Machine Learning.

Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald

Proceedings of the Datenbanksysteme für Business, 2019

2018

On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML.

Matthias Boehm, Berthold Reinwald, Dylan Hutchison, Prithviraj Sen, Alexandre V. Evfimievski, Niketan Pansare

Proc. VLDB Endow., 2018

Deep Learning with Apache SystemML.

Niketan Pansare, Michael Dusenberry, Nakul Jindal, Matthias Boehm, Berthold Reinwald, Prithviraj Sen

CoRR, 2018

On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML.

Matthias Boehm, Berthold Reinwald, Dylan Hutchison, Alexandre V. Evfimievski, Prithviraj Sen

CoRR, 2018

2017

Scaling Machine Learning via Compressed Linear Algebra.

Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald

SIGMOD Rec., 2017

Data Management in Machine Learning: Challenges, Techniques, and Systems.

Arun Kumar, Matthias Boehm, Jun Yang

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

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

Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016

Compressed Linear Algebra for Large-Scale Machine Learning.

Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald

Proc. VLDB Endow., 2016

SystemML: Declarative Machine Learning on Spark.

Matthias Boehm, Michael Dusenberry, Deron Eriksson, Alexandre V. Evfimievski, Faraz Makari Manshadi, Niketan Pansare, Berthold Reinwald, Frederick Reiss, Prithviraj Sen, Arvind Surve, Shirish Tatikonda

Proc. VLDB Endow., 2016

Declarative Machine Learning - A Classification of Basic Properties and Types.

Matthias Boehm, Alexandre V. Evfimievski, Niketan Pansare, Berthold Reinwald

CoRR, 2016

2015

Costing Generated Runtime Execution Plans for Large-Scale Machine Learning Programs.

Matthias Boehm

CoRR, 2015

Resource Elasticity for Large-Scale Machine Learning.

Botong Huang, Matthias Boehm, Yuanyuan Tian, Berthold Reinwald, Shirish Tatikonda, Frederick R. Reiss

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

On optimizing machine learning workloads via kernel fusion.

Arash Ashari, Shirish Tatikonda, Matthias Boehm, Berthold Reinwald, Keith Campbell, John Keenleyside, P. Sadayappan

Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2015

2014

Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML.

Matthias Boehm, Shirish Tatikonda, Berthold Reinwald, Prithviraj Sen, Yuanyuan Tian, Douglas Burdick, Shivakumar Vaithyanathan

Proc. VLDB Endow., 2014

On-demand re-optimization of integration flows.

Matthias Böhm, Dirk Habich, Wolfgang Lehner

Inf. Syst., 2014

SystemML's Optimizer: Plan Generation for Large-Scale Machine Learning Programs.

Matthias Böhm, Douglas R. Burdick, Alexandre V. Evfimievski, Berthold Reinwald, Frederick R. Reiss, Prithviraj Sen, Shirish Tatikonda, Yuanyuan Tian

IEEE Data Eng. Bull., 2014

Large Scale Discriminative Metric Learning.

Peter D. Kirchner, Matthias Böhm, Berthold Reinwald, Daby M. Sow, J. Michael Schmidt, Deepak S. Turaga, Alain Biem

Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

2013

Towards Integrated Data Analytics: Time Series Forecasting in DBMS.

Ulrike Fischer, Lars Dannecker, Laurynas Siksnys, Frank Rosenthal, Matthias Böhm, Wolfgang Lehner

Datenbank-Spektrum, 2013

Compiling machine learning algorithms with SystemML.

Matthias Boehm, Douglas Burdick, Alexandre V. Evfimievski, Berthold Reinwald, Prithviraj Sen, Shirish Tatikonda, Yuanyuan Tian

Proceedings of the ACM Symposium on Cloud Computing, SOCC '13, 2013

2012

A high-throughput in-memory index, durable on flash-based SSD: insights into the winning solution of the SIGMOD programming contest 2011.

Thomas Kissinger, Benjamin Schlegel, Matthias Böhm, Dirk Habich, Wolfgang Lehner

SIGMOD Rec., 2012

Optimizing Notifications of Subscription-Based Forecast Queries.

Ulrike Fischer, Matthias Böhm, Wolfgang Lehner, Torben Bach Pedersen

Proceedings of the Scientific and Statistical Database Management, 2012

Partitioning and Multi-core Parallelization of Multi-equation Forecast Models.

Lars Dannecker, Matthias Böhm, Wolfgang Lehner, Gregor Hackenbroich

Proceedings of the Scientific and Statistical Database Management, 2012

Data management in the MIRABEL smart grid system.

Matthias Böhm, Lars Dannecker, Andreas Doms, Erik Dovgan, Bogdan Filipic, Ulrike Fischer, Wolfgang Lehner, Torben Bach Pedersen, Yoann Pitarch, Laurynas Siksnys, Tea Tusar

Proceedings of the 2012 Joint EDBT/ICDT Workshops, Berlin, Germany, March 30, 2012, 2012

Efficient Integration of External Information into Forecast Models from the Energy Domain.

Lars Dannecker, Elena Vasilyeva, Matthias Böhm, Wolfgang Lehner, Gregor Hackenbroich

Proceedings of the Advances in Databases and Information Systems, 2012

2011

Cost-based optimization of integration flows.

Matthias Böhm

PhD thesis, 2011

Resiliency-Aware Data Management.

Matthias Böhm, Wolfgang Lehner, Christof Fetzer

Proc. VLDB Endow., 2011

Cost-based vectorization of instance-based integration processes.

Matthias Böhm, Dirk Habich, Steffen Preissler, Wolfgang Lehner, Uwe Wloka

Inf. Syst., 2011

Context-Aware Parameter Estimation for Forecast Models in the Energy Domain.

Lars Dannecker, Robert Schulze, Matthias Böhm, Wolfgang Lehner, Gregor Hackenbroich

Proceedings of the Scientific and Statistical Database Management, 2011

Next Generation Database Programming and Execution Environment.

Dirk Habich, Matthias Böhm, Maik Thiele, Benjamin Schlegel, Ulrike Fischer, Hannes Voigt, Wolfgang Lehner

Proceedings of the Database Programming Languages, 2011

Offline Design Tuning for Hierarchies of Forecast Models.

Ulrike Fischer, Matthias Böhm, Wolfgang Lehner

Proceedings of the Datenbanksysteme für Business, 2011

Efficient In-Memory Indexing with Generalized Prefix Trees.

Matthias Böhm, Benjamin Schlegel, Peter Benjamin Volk, Ulrike Fischer, Dirk Habich, Wolfgang Lehner

Proceedings of the Datenbanksysteme für Business, 2011

Forcasting Evolving Time Series of Energy Demand and Supply.

Lars Dannecker, Matthias Böhm, Wolfgang Lehner, Gregor Hackenbroich

Proceedings of the Advances in Databases and Information Systems, 2011

2010

Indexing forecast models for matching and maintenance.

Ulrike Fischer, Frank Rosenthal, Matthias Böhm, Wolfgang Lehner

Proceedings of the Fourteenth International Database Engineering and Applications Symposium (IDEAS 2010), 2010

Multi-flow Optimization via Horizontal Message Queue Partitioning.

Matthias Böhm, Dirk Habich, Wolfgang Lehner

Proceedings of the Enterprise Information Systems - 12th International Conference, 2010

Multi-process Optimization Via Horizontal Message Queue Partitioning.

Matthias Böhm, Dirk Habich, Wolfgang Lehner

Proceedings of the ICEIS 2010 - Proceedings of the 12th International Conference on Enterprise Information Systems, Volume 1, DISI, Funchal, Madeira, Portugal, June 8, 2010

2009

Vectorizing Instance-Based Integration Processes.

Matthias Böhm, Dirk Habich, Steffen Preissler, Wolfgang Lehner, Uwe Wloka

Proceedings of the Enterprise Information Systems, 11th International Conference, 2009

Invisible Deployment of Integration Processes.

Matthias Böhm, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the Enterprise Information Systems, 11th International Conference, 2009

Anfragegetriebene Indizierung räumlicher Daten.

Hannes Voigt, Steffen Preißler, Matthias Böhm, Wolfgang Lehner

Proceedings of the 39. Jahrestagung der Gesellschaft für Informatik, Im Focus das Leben, INFORMATIK 2009, Lübeck, Germany, September 28, 2009

GCIP: exploiting the generation and optimization of integration processes.

Matthias Böhm, Uwe Wloka, Dirk Habich, Wolfgang Lehner

Proceedings of the EDBT 2009, 2009

Systemübergreifende Kostennormalisierung für Integrationsprozesse.

Matthias Böhm, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the Datenbanksysteme in Business, 2009

2008

Model-Driven Development of Complex and Data-Intensive Integration Processes.

Matthias Böhm, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the Model-Based Software and Data Integration, 2008

Message Indexing for Document-Oriented Integration Processes.

Matthias Böhm, Uwe Wloka, Dirk Habich, Wolfgang Lehner

Proceedings of the ICEIS 2008, 2008

Model-Driven Generation and Optimization of Complex Integration Processes.

Matthias Böhm, Uwe Wloka, Dirk Habich, Wolfgang Lehner

Proceedings of the ICEIS 2008, 2008

DIPBench: An independent benchmark for Data-Intensive Integration Processes.

Matthias Böhm, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the 24th International Conference on Data Engineering Workshops, 2008

DIPBench Toolsuite: A Framework for Benchmarking Integration Systems.

Matthias Böhm, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the 24th International Conference on Data Engineering, 2008

Workload-based optimization of integration processes.

Matthias Böhm, Uwe Wloka, Dirk Habich, Wolfgang Lehner

Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008

Improving Data Independence, Efficiency and Functional Flexibility of Integration Platforms.

Matthias Böhm, Jürgen Bittner, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the Forum at the CAiSE'08 Conference, Montpellier, France, June 18-20, 2008, 2008

An Advanced Transaction Model for Recovery Processing of Integration Processes.

Matthias Böhm, Dirk Habich, Wolfgang Lehner, Uwe Wloka

Proceedings of the Advances in Databases and Information Systems, 2008

2007

Ein Nachrichtentransformationsmodell für komplexe Transformationsprozesse in datenzentrischen Anwendungsszenarien.

Matthias Böhm, Jürgen Bittner, Uwe Wloka, Dirk Habich, Wolfgang Lehner

Proceedings of the Datenbanksysteme in Business, 2007

Towards Self-Optimization of Message Transformation Processes.

Matthias Böhm, Dirk Habich, Uwe Wloka, Jürgen Bittner, Wolfgang Lehner

Proceedings of the Communications of the Eleventh East-European Conference on Advances in Databases and Information Systems, Varna, Bulgaria, September 29, 2007