Seguir
Matthias Boehm
Título
Citado por
Citado por
Año
Systemml: Declarative machine learning on spark
M Boehm, MW Dusenberry, D Eriksson, AV Evfimievski, FM Manshadi, ...
Proceedings of the VLDB Endowment 9 (13), 1425-1436, 2016
2442016
Data management in machine learning: Challenges, techniques, and systems
A Kumar, M Boehm, J Yang
Proceedings of the 2017 ACM International Conference on Management of Data …, 2017
1602017
Hybrid parallelization strategies for large-scale machine learning in systemml
M Boehm, S Tatikonda, B Reinwald, P Sen, Y Tian, DR Burdick, ...
Proceedings of the VLDB Endowment 7 (7), 553-564, 2014
1092014
Compressed linear algebra for large-scale machine learning
A Elgohary, M Boehm, PJ Haas, FR Reiss, B Reinwald
Proceedings of the VLDB Endowment 9 (12), 960-971, 2016
912016
Data management in the mirabel smart grid system
M Boehm, L Dannecker, A Doms, E Dovgan, B Filipič, U Fischer, ...
Proceedings of the 2012 Joint EDBT/ICDT Workshops, 95-102, 2012
842012
Efficient in-memory indexing with generalized prefix trees
M Boehm, B Schlegel, PB Volk, U Fischer, D Habich, W Lehner
Gesellschaft für Informatik eV, 2011
822011
Resource elasticity for large-scale machine learning
B Huang, M Boehm, Y Tian, B Reinwald, S Tatikonda, FR Reiss
Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015
732015
On optimizing operator fusion plans for large-scale machine learning in systemml
M Boehm, B Reinwald, D Hutchison, AV Evfimievski, P Sen
arXiv preprint arXiv:1801.00829, 2018
682018
SystemDS: A declarative machine learning system for the end-to-end data science lifecycle
M Boehm, I Antonov, S Baunsgaard, M Dokter, R Ginthör, K Innerebner, ...
arXiv preprint arXiv:1909.02976, 2019
622019
Data management in machine learning systems
M Boehm, A Kumar, J Yang
Springer Nature, 2022
612022
On optimizing machine learning workloads via kernel fusion
A Ashari, S Tatikonda, M Boehm, B Reinwald, K Campbell, J Keenleyside, ...
ACM SIGPLAN Notices 50 (8), 173-182, 2015
562015
SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning.
T Elgamal, S Luo, M Boehm, AV Evfimievski, S Tatikonda, B Reinwald, ...
CIDR, 2017
532017
SystemML's Optimizer: Plan Generation for Large-Scale Machine Learning Programs.
M Boehm, DR Burdick, AV Evfimievski, B Reinwald, FR Reiss, P Sen, ...
IEEE Data Eng. Bull. 37 (3), 52-62, 2014
472014
Sliceline: Fast, linear-algebra-based slice finding for ml model debugging
S Sagadeeva, M Boehm
Proceedings of the 2021 International Conference on Management of Data, 2290 …, 2021
412021
Pipelined approach to fused kernels for optimization of machine learning workloads on graphical processing units
A Ashari, M Boehm, KW Campbell, A Evfimievski, JD Keenleyside, ...
US Patent 9,972,063, 2018
322018
Context-aware parameter estimation for forecast models in the energy domain
L Dannecker, R Schulze, M Böhm, W Lehner, G Hackenbroich
Scientific and Statistical Database Management: 23rd International …, 2011
322011
Compressed linear algebra for large-scale machine learning
A Elgohary, M Boehm, PJ Haas, FR Reiss, B Reinwald
The VLDB Journal 27 (5), 719-744, 2018
302018
Declarative machine learning-a classification of basic properties and types
M Boehm, AV Evfimievski, N Pansare, B Reinwald
arXiv preprint arXiv:1605.05826, 2016
302016
Hybrid parallelization strategies for machine learning programs on top of MapReduce
M Boehm, D Burdick, B Reinwald, P Sen, S Tatikonda, Y Tian, ...
US Patent 9,286,044, 2016
302016
Lima: Fine-grained lineage tracing and reuse in machine learning systems
A Phani, B Rath, M Boehm
Proceedings of the 2021 International Conference on Management of Data, 1426 …, 2021
272021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20